# europe_swit107 - Arosa GR Rot Tritt North - 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/4316
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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_swit107 - Arosa GR Rot Tritt North - 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: Arosa GR Rot Tritt North
#	Location:
#	Country: Switzerland
#	Northernmost_Latitude: 46.8
#	Southernmost_Latitude: 46.8
#	Easternmost_Longitude: 9.68
#	Westernmost_Longitude: 9.68
#	Elevation: 1940 m
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# Data_Collection
#	Collection_Name: europe_swit107B
#	Earliest_Year: 1842
#	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":"5.33204771581","T2":"17.0560613667","M1":"0.0224935680059","M2":"0.41096455364"}}
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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
1842	1.016
1843	0.675
1844	0.816
1845	0.904
1846	1.268
1847	0.909
1848	1.099
1849	1.145
1850	0.973
1851	0.895
1852	0.916
1853	1.034
1854	0.868
1855	1.018
1856	1.052
1857	1.265
1858	0.944
1859	1.199
1860	0.776
1861	1.062
1862	0.908
1863	1.21
1864	1.135
1865	1.0
1866	0.978
1867	1.164
1868	1.147
1869	1.172
1870	1.144
1871	1.043
1872	0.936
1873	1.07
1874	1.074
1875	1.074
1876	1.08
1877	1.15
1878	0.918
1879	0.899
1880	1.041
1881	1.183
1882	0.986
1883	0.903
1884	0.864
1885	1.08
1886	0.855
1887	1.088
1888	0.774
1889	1.023
1890	0.681
1891	0.681
1892	0.75
1893	0.781
1894	0.897
1895	0.906
1896	0.827
1897	0.951
1898	0.725
1899	0.728
1900	0.961
1901	1.058
1902	0.809
1903	1.069
1904	1.437
1905	1.194
1906	0.837
1907	0.892
1908	1.059
1909	0.733
1910	0.895
1911	1.135
1912	0.716
1913	0.629
1914	0.841
1915	0.872
1916	0.827
1917	1.07
1918	0.671
1919	0.972
1920	0.95
1921	1.241
1922	1.022
1923	1.17
1924	0.829
1925	0.982
1926	0.863
1927	1.094
1928	1.237
1929	0.943
1930	1.043
1931	1.311
1932	0.977
1933	0.71
1934	0.698
1935	0.872
1936	0.694
1937	0.948
1938	0.999
1939	0.974
1940	0.882
1941	1.058
1942	1.094
1943	1.111
1944	1.063
1945	1.051
1946	1.129
1947	1.268
1948	0.678
1949	1.247
1950	1.175
1951	1.237
1952	1.383
1953	0.904
1954	0.846
1955	1.153
1956	0.922
1957	0.967
1958	1.032
1959	1.068
1960	1.068
1961	1.224
1962	1.12
1963	1.003
1964	1.045
1965	0.918
1966	1.074
1967	1.226
1968	1.048
1969	1.09
1970	1.202
1971	1.071
1972	0.884
1973	1.133
1974	0.859
1975	0.805