# europe_ital011 - Mount Pollino - 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/4541
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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_ital011 - Mount Pollino - 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 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: Mount Pollino
#	Location:
#	Country: Italy
#	Northernmost_Latitude: 39.9
#	Southernmost_Latitude: 39.9
#	Easternmost_Longitude: 16.2
#	Westernmost_Longitude: 16.2
#	Elevation: 1720 m
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# Data_Collection
#	Collection_Name: europe_ital011B
#	Earliest_Year: 1830
#	Most_Recent_Year: 1980
#	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":"5.22282020082","T2":"16.6716756557","M1":"0.0220933770537","M2":"0.222903862795"}}
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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
1830	0.764
1831	0.789
1832	1.019
1833	0.93
1834	0.848
1835	0.76
1836	0.719
1837	0.926
1838	0.763
1839	0.784
1840	0.692
1841	0.686
1842	0.729
1843	0.719
1844	0.81
1845	0.732
1846	0.862
1847	0.76
1848	0.732
1849	0.92
1850	0.721
1851	1.0
1852	0.804
1853	0.617
1854	0.638
1855	0.859
1856	0.667
1857	0.401
1858	0.691
1859	0.745
1860	0.575
1861	0.611
1862	0.838
1863	0.775
1864	0.976
1865	1.031
1866	1.25
1867	1.035
1868	0.989
1869	0.888
1870	1.301
1871	1.62
1872	1.42
1873	1.595
1874	1.059
1875	1.016
1876	1.568
1877	1.134
1878	0.853
1879	0.762
1880	0.779
1881	0.905
1882	0.652
1883	1.074
1884	1.23
1885	1.286
1886	1.064
1887	1.343
1888	1.085
1889	1.069
1890	1.089
1891	0.997
1892	1.18
1893	1.194
1894	0.931
1895	0.948
1896	0.953
1897	1.341
1898	1.06
1899	1.663
1900	1.378
1901	1.484
1902	1.487
1903	1.136
1904	1.451
1905	1.293
1906	1.159
1907	1.063
1908	1.123
1909	1.281
1910	1.414
1911	1.042
1912	1.026
1913	0.898
1914	0.753
1915	0.931
1916	0.72
1917	0.84
1918	0.561
1919	0.561
1920	0.57
1921	0.603
1922	0.848
1923	1.003
1924	0.856
1925	1.057
1926	1.264
1927	0.911
1928	0.913
1929	0.769
1930	1.575
1931	1.076
1932	0.854
1933	0.923
1934	1.482
1935	0.986
1936	1.199
1937	1.084
1938	0.9
1939	0.838
1940	0.952
1941	0.98
1942	1.2
1943	1.101
1944	1.075
1945	0.951
1946	1.004
1947	1.098
1948	1.129
1949	1.136
1950	1.331
1951	1.141
1952	1.348
1953	1.007
1954	0.791
1955	0.786
1956	0.857
1957	0.614
1958	0.645
1959	0.945
1960	0.902
1961	0.976
1962	0.765
1963	0.891
1964	1.113
1965	0.675
1966	0.976
1967	0.972
1968	1.044
1969	1.218
1970	1.227
1971	1.246
1972	1.094
1973	1.008
1974	0.761
1975	0.898
1976	0.819
1977	0.76
1978	0.641
1979	0.684
1980	0.562