# europe_aust006 - Mariazell Gemeindealpe - 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/4525
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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_aust006 - Mariazell Gemeindealpe - 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: Mariazell Gemeindealpe
#	Location:
#	Country: Austria
#	Northernmost_Latitude: 47.78
#	Southernmost_Latitude: 47.78
#	Easternmost_Longitude: 15.3
#	Westernmost_Longitude: 15.3
#	Elevation: 1380 m
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# Data_Collection
#	Collection_Name: europe_aust006B
#	Earliest_Year: 1843
#	Most_Recent_Year: 1975
#	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":"5.35701708409","T2":"15.4492924926","M1":"0.0222280226252","M2":"0.435669740299"}}
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# Species
#	Species_Name: Norway spruce
#	Species_Code: PCAB
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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
1843	1.051
1844	0.956
1845	1.133
1846	1.173
1847	1.009
1848	0.784
1849	0.56
1850	0.809
1851	0.958
1852	1.159
1853	1.13
1854	1.054
1855	0.972
1856	0.737
1857	0.891
1858	0.981
1859	0.919
1860	0.911
1861	0.913
1862	1.165
1863	0.935
1864	0.984
1865	0.87
1866	1.079
1867	1.255
1868	1.019
1869	1.157
1870	1.166
1871	0.926
1872	0.749
1873	0.984
1874	0.868
1875	1.039
1876	1.001
1877	0.947
1878	0.804
1879	0.889
1880	1.019
1881	1.191
1882	1.087
1883	0.93
1884	0.888
1885	0.755
1886	0.777
1887	0.957
1888	0.991
1889	1.133
1890	1.155
1891	0.996
1892	1.091
1893	1.044
1894	1.205
1895	1.2
1896	1.206
1897	1.088
1898	0.959
1899	1.026
1900	0.877
1901	0.783
1902	0.893
1903	1.013
1904	0.872
1905	1.025
1906	0.806
1907	0.874
1908	0.907
1909	0.92
1910	1.009
1911	0.969
1912	0.912
1913	0.859
1914	0.923
1915	1.045
1916	1.245
1917	1.196
1918	1.152
1919	1.181
1920	1.089
1921	1.172
1922	0.974
1923	1.07
1924	1.256
1925	1.237
1926	1.077
1927	1.204
1928	0.937
1929	0.804
1930	0.765
1931	0.955
1932	1.086
1933	0.921
1934	1.134
1935	1.118
1936	1.028
1937	1.129
1938	1.055
1939	1.007
1940	1.087
1941	1.098
1942	1.011
1943	0.867
1944	1.133
1945	1.037
1946	1.239
1947	1.028
1948	0.628
1949	0.803
1950	0.688
1951	0.844
1952	0.835
1953	1.02
1954	0.907
1955	1.056
1956	1.002
1957	1.033
1958	0.79
1959	0.852
1960	0.865
1961	1.014
1962	0.993
1963	1.024
1964	0.99
1965	0.89
1966	1.122
1967	1.147
1968	0.973
1969	1.07
1970	1.001
1971	0.919
1972	0.917
1973	0.858
1974	0.584
1975	0.814