# europe_aust111 - Parapluiberg - 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/5058
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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
#--------------------
# Title
#	Study_Name: europe_aust111 - Parapluiberg - 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.
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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: Parapluiberg
#	Location:
#	Country: Austria
#	Northernmost_Latitude: 48.12
#	Southernmost_Latitude: 48.12
#	Easternmost_Longitude: 16.25
#	Westernmost_Longitude: 16.25
#	Elevation: 450 m
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# Data_Collection
#	Collection_Name: europe_aust111B
#	Earliest_Year: 1781
#	Most_Recent_Year: 1995
#	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":"4.26180437316","T2":"15.6802855106","M1":"0.0227411286701","M2":"0.574703135584"}}
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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
1781	1.011
1782	0.954
1783	1.021
1784	1.017
1785	1.333
1786	1.129
1787	1.003
1788	1.052
1789	0.575
1790	0.522
1791	1.21
1792	1.083
1793	1.373
1794	1.003
1795	0.98
1796	1.101
1797	0.603
1798	1.033
1799	0.804
1800	0.6
1801	1.087
1802	0.422
1803	0.728
1804	0.817
1805	0.724
1806	0.432
1807	0.72
1808	0.657
1809	0.872
1810	0.94
1811	0.755
1812	1.103
1813	1.331
1814	1.336
1815	1.326
1816	1.404
1817	1.328
1818	1.094
1819	1.243
1820	1.258
1821	1.875
1822	1.053
1823	1.547
1824	1.94
1825	1.492
1826	1.683
1827	0.983
1828	1.282
1829	1.811
1830	1.134
1831	1.754
1832	1.039
1833	0.852
1834	0.769
1835	0.515
1836	0.728
1837	1.332
1838	0.759
1839	0.761
1840	1.231
1841	0.789
1842	0.823
1843	1.443
1844	0.879
1845	1.255
1846	1.343
1847	1.211
1848	1.114
1849	0.667
1850	0.944
1851	1.238
1852	0.639
1853	1.081
1854	0.816
1855	0.888
1856	0.777
1857	0.541
1858	0.491
1859	0.696
1860	0.734
1861	1.057
1862	0.792
1863	0.435
1864	0.922
1865	0.493
1866	0.583
1867	0.98
1868	0.689
1869	0.478
1870	0.81
1871	1.109
1872	0.689
1873	0.644
1874	0.702
1875	0.534
1876	0.877
1877	0.719
1878	0.999
1879	1.015
1880	0.794
1881	0.837
1882	0.695
1883	0.822
1884	1.238
1885	0.989
1886	0.879
1887	0.661
1888	0.811
1889	0.562
1890	0.708
1891	0.515
1892	0.904
1893	0.61
1894	0.828
1895	0.929
1896	0.776
1897	1.248
1898	1.208
1899	1.217
1900	1.067
1901	0.557
1902	1.351
1903	1.698
1904	0.962
1905	0.753
1906	1.297
1907	0.774
1908	0.858
1909	0.805
1910	1.103
1911	1.124
1912	1.826
1913	1.571
1914	1.754
1915	0.938
1916	1.686
1917	0.823
1918	1.291
1919	1.632
1920	1.764
1921	1.027
1922	0.482
1923	0.98
1924	0.745
1925	0.94
1926	1.396
1927	1.075
1928	1.093
1929	0.707
1930	0.561
1931	0.858
1932	1.26
1933	0.899
1934	0.513
1935	0.708
1936	1.151
1937	0.828
1938	0.873
1939	1.534
1940	1.364
1941	1.823
1942	1.438
1943	1.326
1944	1.088
1945	0.361
1946	0.552
1947	0.554
1948	0.494
1949	0.776
1950	0.696
1951	0.935
1952	0.865
1953	1.126
1954	1.021
1955	0.914
1956	0.831
1957	0.736
1958	1.202
1959	1.739
1960	1.265
1961	1.418
1962	0.926
1963	0.861
1964	0.804
1965	1.687
1966	1.305
1967	1.052
1968	0.552
1969	0.904
1970	1.245
1971	0.893
1972	1.367
1973	1.689
1974	0.857
1975	0.889
1976	0.589
1977	0.414
1978	0.846
1979	0.407
1980	0.6
1981	0.671
1982	0.862
1983	0.616
1984	0.541
1985	0.831
1986	0.813
1987	0.768
1988	0.485
1989	1.033
1990	0.968
1991	1.124
1992	1.013
1993	0.661
1994	1.668
1995	1.381