# europe_swit193 - Vals GR Riefawald - 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/8499
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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_swit193 - Vals GR Riefawald - 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: Vals GR Riefawald
#	Location:
#	Country: Switzerland
#	Northernmost_Latitude: 46.62
#	Southernmost_Latitude: 46.62
#	Easternmost_Longitude: 9.2
#	Westernmost_Longitude: 9.2
#	Elevation: 1900 m
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# Data_Collection
#	Collection_Name: europe_swit193B
#	Earliest_Year: 1802
#	Most_Recent_Year: 2008
#	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":"4.44819853489","T2":"16.9931182713","M1":"0.02278164975","M2":"0.391842905179"}}
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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
#
age	trsgi
1802	1.082
1803	1.02
1804	0.901
1805	0.902
1806	0.986
1807	1.245
1808	1.093
1809	1.074
1810	1.073
1811	1.45
1812	1.156
1813	0.804
1814	0.941
1815	0.664
1816	0.671
1817	0.708
1818	0.425
1819	0.381
1820	0.459
1821	0.413
1822	0.811
1823	0.692
1824	0.863
1825	0.809
1826	1.024
1827	1.07
1828	1.279
1829	1.401
1830	1.025
1831	1.224
1832	1.037
1833	1.016
1834	1.248
1835	1.219
1836	1.004
1837	0.915
1838	0.726
1839	0.919
1840	0.927
1841	1.001
1842	1.191
1843	0.798
1844	0.992
1845	1.025
1846	1.381
1847	0.862
1848	0.973
1849	0.843
1850	0.829
1851	0.826
1852	0.729
1853	0.981
1854	0.761
1855	0.995
1856	0.991
1857	0.956
1858	0.808
1859	0.958
1860	0.804
1861	0.909
1862	0.821
1863	1.043
1864	0.927
1865	0.817
1866	0.984
1867	1.082
1868	1.031
1869	1.049
1870	1.005
1871	0.994
1872	0.957
1873	1.011
1874	0.967
1875	1.235
1876	1.195
1877	1.075
1878	0.92
1879	0.846
1880	0.886
1881	1.204
1882	1.052
1883	1.082
1884	0.991
1885	0.975
1886	0.791
1887	1.076
1888	0.75
1889	1.055
1890	0.997
1891	1.006
1892	1.095
1893	0.92
1894	1.003
1895	1.079
1896	0.934
1897	1.001
1898	0.915
1899	0.897
1900	1.029
1901	1.252
1902	1.033
1903	1.166
1904	1.429
1905	1.198
1906	0.926
1907	0.845
1908	1.225
1909	0.811
1910	1.064
1911	1.015
1912	0.792
1913	0.74
1914	0.924
1915	1.128
1916	1.089
1917	1.298
1918	0.882
1919	1.182
1920	1.104
1921	1.281
1922	1.196
1923	1.326
1924	1.133
1925	1.072
1926	0.878
1927	1.083
1928	1.143
1929	0.962
1930	0.971
1931	1.176
1932	1.003
1933	0.73
1934	0.738
1935	0.882
1936	0.925
1937	1.042
1938	0.931
1939	1.004
1940	0.906
1941	1.045
1942	1.163
1943	1.095
1944	1.052
1945	1.106
1946	1.114
1947	1.117
1948	0.629
1949	0.912
1950	0.856
1951	0.963
1952	1.173
1953	0.83
1954	0.875
1955	1.238
1956	0.993
1957	0.904
1958	1.123
1959	1.103
1960	1.156
1961	1.246
1962	1.111
1963	1.109
1964	1.213
1965	0.971
1966	1.037
1967	1.123
1968	1.143
1969	1.242
1970	1.109
1971	1.11
1972	0.997
1973	1.092
1974	0.767
1975	0.722
1976	0.797
1977	0.824
1978	0.726
1979	0.921
1980	0.639
1981	0.721
1982	1.019
1983	0.937
1984	0.794
1985	0.887
1986	0.89
1987	0.671
1988	0.809
1989	0.9
1990	0.768
1991	0.877
1992	0.864
1993	1.082
1994	0.977
1995	1.088
1996	0.804
1997	0.728
1998	0.89
1999	0.811
2000	0.988
2001	1.35
2002	1.241
2003	1.157
2004	1.195
2005	1.266
2006	1.278
2007	1.293
2008	1.258