# europe_ital018 - Monza (Milano) - 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/4044
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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_ital018 - Monza (Milano) - 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: Monza (Milano)
#	Location:
#	Country: Italy
#	Northernmost_Latitude: 45.57
#	Southernmost_Latitude: 45.57
#	Easternmost_Longitude: 9.28
#	Westernmost_Longitude: 9.28
#	Elevation: 190 m
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# Data_Collection
#	Collection_Name: europe_ital018B
#	Earliest_Year: 1830
#	Most_Recent_Year: 1990
#	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":"5.92710122245","T2":"15.7157322786","M1":"0.0227413381525","M2":"0.583728680851"}}
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# Species
#	Species_Name: oak
#	Species_Code: QUSP
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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	0.775
1831	0.916
1832	0.993
1833	1.002
1834	0.814
1835	1.087
1836	0.742
1837	0.608
1838	0.929
1839	0.72
1840	1.092
1841	1.339
1842	0.7
1843	0.898
1844	1.054
1845	1.134
1846	1.068
1847	0.813
1848	1.035
1849	0.824
1850	1.138
1851	1.401
1852	0.975
1853	1.029
1854	1.178
1855	0.489
1856	0.642
1857	0.735
1858	0.857
1859	1.08
1860	0.852
1861	0.91
1862	0.896
1863	1.116
1864	0.804
1865	0.796
1866	0.742
1867	1.157
1868	0.873
1869	1.261
1870	0.788
1871	1.27
1872	1.03
1873	1.0
1874	1.442
1875	1.329
1876	1.079
1877	1.008
1878	1.084
1879	0.9
1880	0.886
1881	0.706
1882	0.714
1883	0.79
1884	0.918
1885	0.732
1886	1.084
1887	1.078
1888	1.097
1889	1.397
1890	1.288
1891	1.162
1892	0.827
1893	1.245
1894	0.896
1895	0.826
1896	0.952
1897	0.916
1898	1.332
1899	0.813
1900	1.053
1901	0.993
1902	1.104
1903	1.025
1904	0.821
1905	0.935
1906	0.978
1907	0.61
1908	0.732
1909	0.652
1910	0.592
1911	0.98
1912	0.886
1913	0.776
1914	1.235
1915	1.087
1916	1.198
1917	1.14
1918	1.156
1919	0.532
1920	0.711
1921	0.892
1922	0.686
1923	0.902
1924	0.994
1925	0.944
1926	1.243
1927	1.128
1928	0.542
1929	0.544
1930	0.356
1931	0.69
1932	1.339
1933	1.352
1934	1.139
1935	0.936
1936	0.665
1937	1.274
1938	1.045
1939	0.98
1940	1.128
1941	0.573
1942	0.266
1943	0.453
1944	0.536
1945	0.553
1946	1.167
1947	0.978
1948	0.884
1949	1.239
1950	0.917
1951	1.343
1952	1.366
1953	1.749
1954	1.531
1955	1.544
1956	1.823
1957	1.224
1958	1.385
1959	1.187
1960	1.451
1961	1.424
1962	1.166
1963	0.953
1964	0.939
1965	0.805
1966	1.021
1967	1.192
1968	1.337
1969	1.097
1970	0.665
1971	0.778
1972	0.643
1973	0.82
1974	0.704
1975	0.908
1976	0.759
1977	0.953
1978	0.955
1979	0.926
1980	0.792
1981	1.097
1982	0.814
1983	0.902
1984	0.844
1985	0.888
1986	0.979
1987	1.045
1988	0.683
1989	1.017
1990	0.642