# europe_swit126 - Tatz Stockwald - 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/4679
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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_swit126 - Tatz Stockwald - 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: Tatz Stockwald
#	Location:
#	Country: Switzerland
#	Northernmost_Latitude: 46.33
#	Southernmost_Latitude: 46.33
#	Easternmost_Longitude: 7.78
#	Westernmost_Longitude: 7.78
#	Elevation: 1850 m
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# Data_Collection
#	Collection_Name: europe_swit126B
#	Earliest_Year: 1839
#	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":"3.93404845581","T2":"17.0971530919","M1":"0.02190110201","M2":"0.392694332013"}}
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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
1839	0.916
1840	0.962
1841	1.082
1842	1.168
1843	0.873
1844	1.091
1845	1.043
1846	1.274
1847	1.095
1848	1.062
1849	0.929
1850	0.942
1851	1.107
1852	1.056
1853	1.067
1854	0.991
1855	0.928
1856	0.882
1857	0.806
1858	0.757
1859	0.857
1860	0.636
1861	1.028
1862	0.738
1863	0.972
1864	0.961
1865	0.97
1866	0.988
1867	0.903
1868	1.052
1869	1.158
1870	0.859
1871	1.039
1872	1.066
1873	1.032
1874	0.994
1875	0.976
1876	0.947
1877	1.164
1878	1.045
1879	1.064
1880	0.989
1881	1.091
1882	1.054
1883	0.993
1884	1.003
1885	0.889
1886	0.939
1887	0.848
1888	0.767
1889	1.005
1890	0.977
1891	0.841
1892	1.073
1893	1.129
1894	0.859
1895	0.839
1896	0.82
1897	1.043
1898	1.05
1899	0.874
1900	0.927
1901	0.989
1902	0.947
1903	0.964
1904	0.994
1905	1.034
1906	0.922
1907	0.882
1908	1.202
1909	0.874
1910	0.937
1911	1.051
1912	0.769
1913	0.775
1914	0.867
1915	0.858
1916	0.952
1917	1.038
1918	0.953
1919	1.061
1920	1.261
1921	1.126
1922	1.113
1923	1.184
1924	1.158
1925	1.245
1926	1.122
1927	1.263
1928	1.294
1929	1.208
1930	1.033
1931	1.125
1932	1.081
1933	1.041
1934	1.123
1935	1.074
1936	1.1
1937	1.21
1938	1.236
1939	1.2
1940	1.259
1941	1.198
1942	1.233
1943	1.336
1944	1.089
1945	1.11
1946	1.078
1947	0.878
1948	0.561
1949	0.906
1950	0.75
1951	0.859
1952	1.039
1953	0.953
1954	1.021
1955	1.189
1956	1.031
1957	1.042
1958	1.078
1959	0.978
1960	0.854
1961	0.878
1962	0.654
1963	0.669
1964	0.934
1965	0.703
1966	0.821
1967	0.878
1968	0.893
1969	1.122
1970	0.916
1971	0.787
1972	0.74
1973	0.939
1974	0.743
1975	0.713
1976	0.807
1977	0.9
1978	0.885
1979	0.887
1980	0.764