# europe_swit121 - Mittleri Hellelawald - 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/4531
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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_swit121 - Mittleri Hellelawald - 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: Mittleri Hellelawald
#	Location:
#	Country: Switzerland
#	Northernmost_Latitude: 46.3
#	Southernmost_Latitude: 46.3
#	Easternmost_Longitude: 7.83
#	Westernmost_Longitude: 7.83
#	Elevation: 1510 m
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# Data_Collection
#	Collection_Name: europe_swit121B
#	Earliest_Year: 1836
#	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":"5.71333403446","T2":"16.77645167","M1":"0.0223690052909","M2":"0.392644897201"}}
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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
1836	0.692
1837	0.767
1838	0.919
1839	0.918
1840	0.777
1841	0.728
1842	0.897
1843	1.133
1844	0.983
1845	1.311
1846	1.264
1847	1.079
1848	1.068
1849	0.997
1850	1.045
1851	1.096
1852	1.138
1853	1.24
1854	1.015
1855	0.999
1856	1.11
1857	0.942
1858	0.815
1859	1.045
1860	0.749
1861	0.877
1862	0.724
1863	0.892
1864	0.932
1865	0.691
1866	0.945
1867	0.947
1868	0.751
1869	0.983
1870	0.789
1871	1.05
1872	0.908
1873	1.117
1874	0.826
1875	0.832
1876	1.084
1877	0.842
1878	0.944
1879	0.931
1880	0.829
1881	1.158
1882	1.26
1883	1.34
1884	1.632
1885	1.521
1886	1.602
1887	1.594
1888	0.979
1889	1.435
1890	1.354
1891	1.122
1892	1.303
1893	1.066
1894	0.886
1895	1.044
1896	1.075
1897	1.031
1898	1.114
1899	1.035
1900	0.917
1901	0.906
1902	1.045
1903	1.098
1904	1.093
1905	1.091
1906	1.061
1907	0.954
1908	1.04
1909	0.824
1910	0.959
1911	1.03
1912	0.911
1913	0.806
1914	1.101
1915	0.895
1916	1.094
1917	0.914
1918	1.147
1919	0.844
1920	0.933
1921	0.64
1922	0.66
1923	0.926
1924	0.821
1925	0.863
1926	1.056
1927	0.902
1928	1.008
1929	0.81
1930	0.822
1931	1.057
1932	1.146
1933	0.906
1934	0.792
1935	0.938
1936	0.953
1937	0.984
1938	1.061
1939	0.961
1940	1.102
1941	1.033
1942	0.831
1943	0.936
1944	0.781
1945	0.867
1946	1.045
1947	0.934
1948	0.89
1949	1.21
1950	0.877
1951	1.044
1952	1.181
1953	0.95
1954	1.065
1955	1.153
1956	0.878
1957	1.097
1958	1.079
1959	1.124
1960	0.844
1961	1.185
1962	1.021
1963	0.846
1964	1.021
1965	0.888
1966	0.968
1967	1.097
1968	0.942
1969	1.084
1970	0.877
1971	0.911
1972	1.012
1973	1.034
1974	0.931
1975	0.836
1976	0.939
1977	0.946
1978	1.085
1979	1.001
1980	0.961