# europe_swit124 - Burchen Bielwald - 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/4360
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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
#--------------------
# Title
#	Study_Name: europe_swit124 - Burchen Bielwald - Breitenmoser Tree Ring Chronology Data
#--------------------
# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
#--------------------
# Description_and_Notes
#	Description: Data from Breitenmoser 2014 Journal of past Climate supplementary, see publication for ARSTAN standardization details
#--------------------
# 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:
#--------------------
#	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: Burchen Bielwald
#	Location:
#	Country: Switzerland
#	Northernmost_Latitude: 46.28
#	Southernmost_Latitude: 46.28
#	Easternmost_Longitude: 7.83
#	Westernmost_Longitude: 7.83
#	Elevation: 1740 m
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# Data_Collection
#	Collection_Name: europe_swit124B
#	Earliest_Year: 1715
#	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":"3.87755796264","T2":"17.1376379972","M1":"0.0221335652296","M2":"0.392738647781"}}
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# Species
#	Species_Name: Norway spruce
#	Species_Code: PCAB
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# Chronology:
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# Variables
#
# 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)
#
##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
1715	1.651
1716	1.165
1717	1.253
1718	1.225
1719	1.067
1720	1.015
1721	0.852
1722	1.143
1723	1.2
1724	0.906
1725	0.8
1726	1.061
1727	0.77
1728	0.978
1729	0.977
1730	1.111
1731	0.829
1732	0.956
1733	1.016
1734	0.78
1735	0.87
1736	1.058
1737	1.027
1738	0.863
1739	1.022
1740	0.969
1741	0.946
1742	0.741
1743	0.836
1744	0.909
1745	0.905
1746	0.735
1747	0.675
1748	0.824
1749	0.695
1750	0.602
1751	0.927
1752	0.842
1753	0.831
1754	0.987
1755	0.591
1756	0.805
1757	0.691
1758	0.617
1759	0.819
1760	0.729
1761	0.736
1762	0.443
1763	0.804
1764	0.8
1765	0.694
1766	0.815
1767	0.678
1768	0.724
1769	0.772
1770	0.802
1771	0.806
1772	0.903
1773	0.574
1774	0.863
1775	0.805
1776	0.969
1777	0.827
1778	0.948
1779	0.632
1780	0.808
1781	0.883
1782	0.735
1783	0.601
1784	0.702
1785	0.626
1786	0.751
1787	0.714
1788	0.577
1789	0.4
1790	0.635
1791	0.53
1792	0.528
1793	0.597
1794	0.589
1795	0.559
1796	0.626
1797	0.673
1798	0.634
1799	0.579
1800	0.54
1801	0.643
1802	0.75
1803	0.528
1804	0.58
1805	0.609
1806	0.594
1807	0.749
1808	0.591
1809	0.607
1810	0.611
1811	0.773
1812	0.701
1813	0.699
1814	0.655
1815	0.708
1816	0.547
1817	0.73
1818	0.727
1819	0.891
1820	0.805
1821	0.766
1822	1.165
1823	1.276
1824	1.245
1825	1.379
1826	1.203
1827	1.083
1828	1.123
1829	1.154
1830	1.002
1831	0.937
1832	0.889
1833	0.973
1834	0.994
1835	0.867
1836	0.959
1837	0.855
1838	0.818
1839	0.84
1840	1.078
1841	1.109
1842	1.104
1843	1.023
1844	1.115
1845	1.119
1846	1.43
1847	1.509
1848	1.63
1849	1.544
1850	1.507
1851	1.392
1852	1.354
1853	1.387
1854	1.379
1855	1.333
1856	1.356
1857	1.076
1858	0.983
1859	0.988
1860	0.846
1861	0.947
1862	0.954
1863	1.14
1864	1.191
1865	1.135
1866	1.191
1867	1.256
1868	1.223
1869	1.14
1870	1.118
1871	1.198
1872	1.124
1873	1.244
1874	1.147
1875	1.179
1876	1.146
1877	1.094
1878	1.204
1879	1.093
1880	1.152
1881	1.261
1882	1.369
1883	1.281
1884	1.055
1885	0.951
1886	0.906
1887	0.973
1888	0.946
1889	1.031
1890	1.034
1891	0.94
1892	1.211
1893	1.078
1894	0.953
1895	1.005
1896	1.034
1897	1.126
1898	1.067
1899	1.185
1900	1.127
1901	1.141
1902	1.119
1903	1.019
1904	1.058
1905	0.897
1906	0.816
1907	0.745
1908	1.126
1909	0.772
1910	0.952
1911	1.07
1912	0.862
1913	0.828
1914	0.861
1915	0.92
1916	0.864
1917	1.046
1918	0.874
1919	1.021
1920	0.972
1921	0.996
1922	0.842
1923	0.884
1924	0.936
1925	1.0
1926	1.004
1927	1.091
1928	1.032
1929	1.033
1930	0.98
1931	1.062
1932	1.015
1933	0.825
1934	1.054
1935	0.991
1936	1.047
1937	1.043
1938	1.057
1939	0.978
1940	1.008
1941	1.02
1942	1.05
1943	1.102
1944	1.029
1945	0.965
1946	0.971
1947	1.054
1948	0.73
1949	0.935
1950	0.858
1951	1.116
1952	1.043
1953	1.005
1954	0.938
1955	1.138
1956	0.958
1957	1.011
1958	0.995
1959	0.97
1960	0.906
1961	0.91
1962	0.784
1963	0.882
1964	0.929
1965	0.8
1966	0.877
1967	0.877
1968	0.813
1969	0.943
1970	0.877
1971	0.846
1972	0.851
1973	0.97
1974	0.697
1975	0.689
1976	0.688
1977	0.819
1978	0.727
1979	0.917
1980	0.745