# europe_norw006 - Veolia - 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/4713
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: europe_norw006 - Veolia - 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: Veolia
#	Location:
#	Country: Norway
#	Northernmost_Latitude: 61.42
#	Southernmost_Latitude: 61.42
#	Easternmost_Longitude: 8.98
#	Westernmost_Longitude: 8.98
#	Elevation: 880 m
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# Data_Collection
#	Collection_Name: europe_norw006B
#	Earliest_Year: 1780
#	Most_Recent_Year: 1978
#	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":"5.06353617926","T2":"17.9720817915","M1":"0.0222141859774","M2":"0.383804725459"}}
#--------------------
# Species
#	Species_Name: Scots pine
#	Species_Code: PISY
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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)
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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
1780	0.862
1781	0.663
1782	0.618
1783	0.254
1784	0.355
1785	0.5
1786	0.55
1787	0.704
1788	0.683
1789	0.595
1790	0.666
1791	0.65
1792	0.907
1793	1.114
1794	1.252
1795	1.092
1796	0.875
1797	1.4
1798	1.211
1799	1.093
1800	0.792
1801	1.099
1802	0.722
1803	0.567
1804	0.931
1805	0.929
1806	0.733
1807	0.884
1808	0.802
1809	1.04
1810	0.813
1811	1.13
1812	0.798
1813	1.047
1814	1.073
1815	1.055
1816	1.067
1817	0.854
1818	0.893
1819	1.049
1820	0.934
1821	0.736
1822	1.137
1823	0.95
1824	0.886
1825	0.921
1826	1.209
1827	1.153
1828	1.378
1829	1.092
1830	1.132
1831	1.539
1832	0.855
1833	1.133
1834	1.614
1835	0.973
1836	0.78
1837	0.634
1838	0.807
1839	0.815
1840	0.753
1841	0.738
1842	1.01
1843	1.201
1844	0.814
1845	0.891
1846	1.023
1847	1.106
1848	0.958
1849	0.877
1850	1.065
1851	0.83
1852	1.06
1853	0.809
1854	1.295
1855	1.272
1856	0.979
1857	1.008
1858	1.227
1859	1.115
1860	1.114
1861	1.221
1862	1.161
1863	1.287
1864	1.136
1865	0.739
1866	0.969
1867	0.654
1868	0.74
1869	0.612
1870	0.85
1871	0.798
1872	0.81
1873	1.051
1874	1.009
1875	1.295
1876	1.075
1877	0.987
1878	1.237
1879	1.202
1880	1.175
1881	0.809
1882	1.231
1883	1.221
1884	1.171
1885	1.299
1886	0.919
1887	1.229
1888	0.872
1889	0.895
1890	0.837
1891	0.916
1892	1.004
1893	1.096
1894	1.28
1895	1.109
1896	1.362
1897	1.571
1898	1.171
1899	1.347
1900	1.367
1901	1.485
1902	0.999
1903	0.895
1904	1.1
1905	0.686
1906	0.675
1907	0.781
1908	0.828
1909	0.776
1910	1.023
1911	1.026
1912	1.058
1913	1.056
1914	1.585
1915	1.18
1916	1.197
1917	1.356
1918	1.256
1919	1.333
1920	0.946
1921	1.025
1922	0.954
1923	0.706
1924	0.654
1925	0.933
1926	0.771
1927	0.695
1928	0.355
1929	0.789
1930	0.935
1931	0.682
1932	0.622
1933	0.84
1934	1.074
1935	0.954
1936	1.091
1937	1.482
1938	1.366
1939	1.24
1940	0.936
1941	1.214
1942	1.042
1943	1.359
1944	1.395
1945	1.19
1946	1.039
1947	1.179
1948	0.999
1949	0.83
1950	0.805
1951	0.929
1952	1.149
1953	1.188
1954	1.177
1955	1.122
1956	0.74
1957	0.879
1958	0.635
1959	0.824
1960	0.802
1961	0.76
1962	0.885
1963	0.938
1964	0.879
1965	0.749
1966	0.797
1967	0.907
1968	0.864
1969	0.861
1970	0.699
1971	0.724
1972	1.105
1973	1.133
1974	0.77
1975	0.849
1976	0.834
1977	0.663
1978	0.695