# europe_spai013 - Navafria I - 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/5399
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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_spai013 - Navafria I - 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: Navafria I
#	Location:
#	Country: Spain
#	Northernmost_Latitude: 40.02
#	Southernmost_Latitude: 40.02
#	Easternmost_Longitude: -0.12
#	Westernmost_Longitude: -0.12
#	Elevation: 1900 m
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# Data_Collection
#	Collection_Name: europe_spai013B
#	Earliest_Year: 1764
#	Most_Recent_Year: 1992
#	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":"5.69054156566","T2":"17.6586326456","M1":"0.0224021498546","M2":"0.418984912349"}}
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# 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
1764	1.241
1765	1.17
1766	0.899
1767	0.965
1768	0.978
1769	0.7
1770	0.484
1771	0.428
1772	0.559
1773	0.841
1774	0.838
1775	0.785
1776	0.9
1777	0.917
1778	0.946
1779	1.187
1780	1.423
1781	1.376
1782	1.072
1783	0.923
1784	0.697
1785	0.737
1786	1.178
1787	1.253
1788	1.552
1789	1.354
1790	1.179
1791	1.28
1792	1.039
1793	1.427
1794	1.286
1795	1.056
1796	1.006
1797	0.98
1798	1.315
1799	1.036
1800	0.579
1801	0.415
1802	0.459
1803	0.524
1804	0.54
1805	1.068
1806	0.789
1807	0.938
1808	0.773
1809	0.674
1810	0.83
1811	1.038
1812	1.107
1813	1.26
1814	1.108
1815	0.968
1816	0.849
1817	0.944
1818	0.929
1819	1.079
1820	0.922
1821	1.207
1822	1.274
1823	1.144
1824	1.02
1825	1.098
1826	0.875
1827	0.79
1828	0.943
1829	0.87
1830	1.029
1831	0.816
1832	0.739
1833	0.835
1834	1.135
1835	0.879
1836	0.836
1837	1.088
1838	0.972
1839	1.015
1840	1.037
1841	1.205
1842	0.967
1843	1.027
1844	0.894
1845	0.895
1846	1.132
1847	1.008
1848	0.776
1849	0.899
1850	1.011
1851	0.987
1852	0.961
1853	0.926
1854	1.083
1855	0.853
1856	0.9
1857	0.82
1858	1.093
1859	1.367
1860	1.115
1861	1.129
1862	0.898
1863	0.928
1864	1.219
1865	0.987
1866	1.178
1867	1.34
1868	1.257
1869	1.392
1870	1.204
1871	1.265
1872	1.122
1873	1.159
1874	1.057
1875	0.956
1876	0.877
1877	1.0
1878	1.215
1879	0.783
1880	0.877
1881	1.042
1882	1.087
1883	0.972
1884	1.076
1885	1.068
1886	0.968
1887	1.019
1888	1.127
1889	1.153
1890	1.02
1891	0.904
1892	1.044
1893	1.183
1894	0.751
1895	0.721
1896	0.706
1897	0.968
1898	0.999
1899	1.046
1900	0.949
1901	0.81
1902	0.991
1903	1.278
1904	1.407
1905	1.382
1906	1.178
1907	0.965
1908	0.759
1909	0.78
1910	0.895
1911	0.856
1912	1.012
1913	1.055
1914	1.19
1915	1.067
1916	1.078
1917	0.95
1918	1.036
1919	0.972
1920	0.793
1921	0.656
1922	0.882
1923	1.175
1924	0.792
1925	0.854
1926	1.106
1927	1.151
1928	0.945
1929	1.028
1930	0.929
1931	1.153
1932	1.182
1933	1.41
1934	1.024
1935	0.736
1936	0.949
1937	1.213
1938	0.89
1939	0.853
1940	0.869
1941	0.468
1942	0.55
1943	0.909
1944	1.35
1945	1.43
1946	1.031
1947	1.39
1948	1.185
1949	1.052
1950	1.08
1951	1.212
1952	1.105
1953	1.013
1954	0.671
1955	0.809
1956	0.836
1957	0.919
1958	1.229
1959	1.264
1960	0.955
1961	0.884
1962	0.648
1963	0.552
1964	0.918
1965	0.753
1966	0.715
1967	0.713
1968	0.75
1969	0.772
1970	0.885
1971	0.803
1972	0.698
1973	0.995
1974	0.868
1975	0.778
1976	1.123
1977	0.843
1978	0.869
1979	0.837
1980	1.031
1981	0.991
1982	1.055
1983	1.0
1984	0.864
1985	1.029
1986	0.736
1987	0.731
1988	0.76
1989	0.982
1990	0.967
1991	0.769
1992	1.078