# europe_ital019 - Corte Brugnatella (Piacenza) - 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/4042
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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_ital019 - Corte Brugnatella (Piacenza) - 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: Corte Brugnatella (Piacenza)
#	Location:
#	Country: Italy
#	Northernmost_Latitude: 44.72
#	Southernmost_Latitude: 44.72
#	Easternmost_Longitude: 9.32
#	Westernmost_Longitude: 9.32
#	Elevation: 900 m
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# Data_Collection
#	Collection_Name: europe_ital019B
#	Earliest_Year: 1860
#	Most_Recent_Year: 1989
#	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":"4.7676072129","T2":"13.2154495272","M1":"0.0226686048176","M2":"0.598237738845"}}
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# Species
#	Species_Name: English oak
#	Species_Code: QURO
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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
1860	0.779
1861	0.597
1862	0.976
1863	1.12
1864	0.92
1865	0.825
1866	0.826
1867	0.919
1868	1.142
1869	1.328
1870	1.085
1871	1.106
1872	1.073
1873	0.889
1874	0.944
1875	1.498
1876	1.123
1877	0.987
1878	1.075
1879	0.664
1880	0.645
1881	0.664
1882	0.653
1883	1.021
1884	1.165
1885	0.899
1886	1.095
1887	0.974
1888	1.107
1889	1.257
1890	0.915
1891	0.891
1892	0.806
1893	1.115
1894	1.015
1895	1.107
1896	1.017
1897	0.984
1898	1.164
1899	1.498
1900	1.183
1901	1.444
1902	1.022
1903	1.13
1904	1.024
1905	0.983
1906	1.183
1907	0.824
1908	1.068
1909	0.977
1910	0.987
1911	1.212
1912	1.13
1913	0.923
1914	1.203
1915	1.261
1916	1.148
1917	1.317
1918	1.155
1919	0.748
1920	0.733
1921	0.81
1922	0.797
1923	0.701
1924	0.982
1925	0.863
1926	1.001
1927	0.887
1928	0.813
1929	1.098
1930	1.19
1931	0.804
1932	1.057
1933	1.037
1934	0.909
1935	0.769
1936	0.896
1937	0.981
1938	0.804
1939	0.915
1940	1.181
1941	0.996
1942	0.876
1943	0.82
1944	0.966
1945	0.752
1946	0.828
1947	0.89
1948	0.973
1949	0.94
1950	0.543
1951	0.963
1952	0.878
1953	0.872
1954	1.026
1955	1.168
1956	1.084
1957	1.04
1958	0.936
1959	0.787
1960	0.995
1961	1.23
1962	1.047
1963	1.095
1964	0.971
1965	1.048
1966	1.077
1967	1.135
1968	1.341
1969	1.451
1970	0.988
1971	1.158
1972	1.065
1973	1.042
1974	0.851
1975	1.059
1976	0.915
1977	0.738
1978	1.043
1979	1.026
1980	0.939
1981	0.856
1982	0.975
1983	0.962
1984	0.717
1985	0.938
1986	1.129
1987	0.902
1988	1.071
1989	1.014