# europe_spai019 - Riscopal - 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/3288
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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_spai019 - Riscopal - 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: Riscopal
#	Location:
#	Country: Spain
#	Northernmost_Latitude: 40.78
#	Southernmost_Latitude: 40.78
#	Easternmost_Longitude: -4.0
#	Westernmost_Longitude: -4.0
#	Elevation: 1600 m
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# Data_Collection
#	Collection_Name: europe_spai019B
#	Earliest_Year: 1734
#	Most_Recent_Year: 1988
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.46299133711","T2":"15.1793202173","M1":"0.0229880934536","M2":"0.489680071867"}}
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# Species
#	Species_Name: Austrian pine
#	Species_Code: PINI
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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
1734	1.029
1735	1.162
1736	0.961
1737	1.157
1738	1.292
1739	1.175
1740	1.011
1741	1.044
1742	0.789
1743	1.066
1744	1.257
1745	0.74
1746	0.869
1747	0.588
1748	0.926
1749	0.931
1750	0.83
1751	0.925
1752	0.749
1753	0.812
1754	0.85
1755	0.666
1756	0.825
1757	1.159
1758	1.087
1759	0.75
1760	1.032
1761	1.219
1762	1.39
1763	1.337
1764	0.962
1765	1.141
1766	1.157
1767	0.797
1768	0.752
1769	0.449
1770	0.526
1771	0.474
1772	0.669
1773	0.943
1774	0.979
1775	0.871
1776	0.953
1777	0.695
1778	0.781
1779	1.023
1780	0.911
1781	1.102
1782	0.911
1783	1.199
1784	1.022
1785	0.939
1786	1.027
1787	1.094
1788	1.546
1789	0.999
1790	0.986
1791	1.109
1792	1.326
1793	1.216
1794	1.235
1795	1.368
1796	1.2
1797	0.892
1798	0.902
1799	1.046
1800	1.183
1801	1.163
1802	0.954
1803	0.653
1804	1.225
1805	1.301
1806	0.736
1807	0.977
1808	0.798
1809	1.086
1810	1.122
1811	1.459
1812	0.964
1813	1.177
1814	1.359
1815	1.534
1816	1.095
1817	1.068
1818	1.014
1819	1.126
1820	0.849
1821	1.198
1822	1.033
1823	0.974
1824	0.758
1825	1.188
1826	1.235
1827	0.986
1828	1.137
1829	0.984
1830	1.11
1831	0.992
1832	0.724
1833	0.674
1834	0.953
1835	0.875
1836	1.028
1837	1.077
1838	0.739
1839	0.815
1840	0.596
1841	1.0
1842	0.937
1843	1.02
1844	0.985
1845	0.978
1846	1.226
1847	0.881
1848	0.876
1849	1.147
1850	1.174
1851	0.934
1852	0.918
1853	1.018
1854	0.976
1855	0.76
1856	0.937
1857	0.981
1858	0.88
1859	1.067
1860	0.755
1861	1.085
1862	0.755
1863	0.753
1864	1.028
1865	0.844
1866	0.983
1867	0.851
1868	1.102
1869	1.147
1870	0.631
1871	0.887
1872	0.794
1873	0.772
1874	0.909
1875	0.889
1876	0.631
1877	0.823
1878	1.036
1879	0.577
1880	0.9
1881	1.291
1882	1.051
1883	1.002
1884	0.958
1885	1.655
1886	1.57
1887	1.095
1888	1.24
1889	1.347
1890	0.991
1891	1.2
1892	1.033
1893	1.239
1894	0.988
1895	1.138
1896	1.162
1897	1.131
1898	1.002
1899	1.102
1900	0.619
1901	0.771
1902	1.022
1903	1.321
1904	1.16
1905	1.076
1906	1.036
1907	0.922
1908	0.828
1909	0.971
1910	1.081
1911	1.13
1912	1.201
1913	0.919
1914	1.371
1915	0.959
1916	0.899
1917	0.751
1918	0.818
1919	1.012
1920	1.064
1921	0.854
1922	0.801
1923	1.014
1924	0.796
1925	1.182
1926	1.473
1927	0.95
1928	0.914
1929	1.294
1930	1.376
1931	1.025
1932	1.484
1933	1.681
1934	0.683
1935	0.692
1936	0.999
1937	1.212
1938	0.874
1939	0.715
1940	1.395
1941	0.953
1942	0.563
1943	0.757
1944	0.825
1945	0.809
1946	0.549
1947	0.728
1948	0.852
1949	0.779
1950	0.992
1951	1.047
1952	1.239
1953	1.083
1954	0.826
1955	0.984
1956	0.978
1957	1.093
1958	1.066
1959	0.976
1960	0.986
1961	0.943
1962	0.704
1963	0.659
1964	0.83
1965	0.498
1966	0.652
1967	0.624
1968	0.644
1969	0.761
1970	0.854
1971	0.749
1972	0.613
1973	0.862
1974	0.668
1975	0.706
1976	0.909
1977	1.26
1978	1.204
1979	0.793
1980	1.225
1981	0.909
1982	1.015
1983	1.267
1984	1.212
1985	0.922
1986	0.578
1987	1.185
1988	1.18