# europe_spai016 - Penahorcada - 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/3287
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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_spai016 - Penahorcada - 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: Penahorcada
#	Location:
#	Country: Spain
#	Northernmost_Latitude: 40.48
#	Southernmost_Latitude: 40.48
#	Easternmost_Longitude: -4.78
#	Westernmost_Longitude: -4.78
#	Elevation: 1450 m
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# Data_Collection
#	Collection_Name: europe_spai016B
#	Earliest_Year: 1787
#	Most_Recent_Year: 1988
#	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":"4.48976249775","T2":"15.0054819601","M1":"0.0218773122113","M2":"0.304405176331"}}
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# Species
#	Species_Name: Austrian pine
#	Species_Code: PINI
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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
1787	0.826
1788	1.138
1789	0.955
1790	1.045
1791	1.285
1792	1.221
1793	1.168
1794	1.532
1795	1.448
1796	1.179
1797	1.053
1798	1.045
1799	1.287
1800	1.045
1801	0.774
1802	0.635
1803	0.521
1804	0.76
1805	0.95
1806	0.914
1807	1.151
1808	0.999
1809	1.18
1810	1.223
1811	1.239
1812	0.671
1813	0.523
1814	0.875
1815	1.129
1816	0.861
1817	1.033
1818	0.93
1819	1.046
1820	1.036
1821	1.052
1822	1.106
1823	1.157
1824	1.034
1825	1.377
1826	1.188
1827	0.903
1828	1.16
1829	0.953
1830	0.874
1831	0.738
1832	0.7
1833	0.744
1834	1.275
1835	1.131
1836	1.111
1837	1.057
1838	0.786
1839	0.912
1840	0.812
1841	0.773
1842	0.704
1843	0.821
1844	0.917
1845	0.973
1846	1.303
1847	0.69
1848	0.622
1849	0.809
1850	1.124
1851	0.79
1852	0.849
1853	1.041
1854	0.95
1855	0.719
1856	1.024
1857	0.761
1858	1.08
1859	1.268
1860	0.939
1861	1.239
1862	0.966
1863	1.373
1864	1.389
1865	1.325
1866	1.056
1867	0.923
1868	0.899
1869	1.186
1870	0.677
1871	0.541
1872	0.714
1873	0.647
1874	0.702
1875	0.859
1876	0.824
1877	1.087
1878	1.293
1879	0.691
1880	1.06
1881	1.237
1882	1.116
1883	1.273
1884	1.033
1885	1.482
1886	1.379
1887	1.031
1888	1.178
1889	0.921
1890	0.693
1891	0.629
1892	0.948
1893	1.036
1894	0.781
1895	1.067
1896	1.098
1897	0.928
1898	1.013
1899	1.197
1900	0.836
1901	0.644
1902	0.928
1903	1.411
1904	1.13
1905	1.019
1906	0.965
1907	0.911
1908	0.815
1909	0.693
1910	0.83
1911	0.948
1912	1.051
1913	0.946
1914	1.384
1915	0.787
1916	0.885
1917	0.733
1918	0.706
1919	1.048
1920	1.115
1921	0.908
1922	0.862
1923	1.188
1924	0.699
1925	0.824
1926	1.033
1927	0.853
1928	0.843
1929	1.103
1930	1.198
1931	0.86
1932	0.861
1933	1.026
1934	0.6
1935	0.528
1936	0.815
1937	1.194
1938	1.119
1939	1.039
1940	1.622
1941	0.9
1942	0.548
1943	0.863
1944	0.898
1945	1.144
1946	0.701
1947	0.839
1948	0.952
1949	0.815
1950	1.082
1951	0.986
1952	1.181
1953	1.268
1954	1.03
1955	0.988
1956	0.832
1957	1.209
1958	1.154
1959	1.151
1960	1.163
1961	1.211
1962	0.742
1963	0.697
1964	1.277
1965	0.762
1966	0.826
1967	1.008
1968	0.855
1969	0.974
1970	0.995
1971	0.96
1972	0.844
1973	1.491
1974	1.247
1975	1.022
1976	1.32
1977	1.397
1978	1.285
1979	0.795
1980	1.141
1981	0.856
1982	0.909
1983	1.185
1984	1.155
1985	1.02
1986	0.671
1987	1.04
1988	1.293