# europe_finl065 - Pisa - 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/2843
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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_finl065 - Pisa - 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.
#--------------------
#	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: Pisa
#	Location:
#	Country: Finland
#	Northernmost_Latitude: 66.32
#	Southernmost_Latitude: 66.32
#	Easternmost_Longitude: 25.15
#	Westernmost_Longitude: 25.15
#	Elevation: 160 m
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# Data_Collection
#	Collection_Name: europe_finl065B
#	Earliest_Year: 1734
#	Most_Recent_Year: 1983
#	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":"5.0065520244","T2":"17.0514746851","M1":"0.0230960820703","M2":"0.393237727486"}}
#--------------------
# 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)
#
##age	age, , ,years AD, , , , ,N
##trsgi	tree ring standardized growth index, tree ring, ,percent relative to mean growth, , Tree Rings, , ,N
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1734	0.845
1735	0.742
1736	0.541
1737	0.433
1738	0.429
1739	0.487
1740	0.443
1741	0.362
1742	0.459
1743	0.52
1744	0.665
1745	0.663
1746	0.617
1747	0.549
1748	0.626
1749	0.536
1750	0.449
1751	0.45
1752	0.746
1753	0.779
1754	0.918
1755	1.078
1756	1.014
1757	1.123
1758	0.944
1759	0.873
1760	0.901
1761	0.86
1762	0.85
1763	0.789
1764	0.807
1765	0.813
1766	0.771
1767	0.48
1768	0.405
1769	0.472
1770	0.643
1771	0.616
1772	0.79
1773	1.097
1774	1.23
1775	1.131
1776	0.939
1777	1.031
1778	1.444
1779	1.516
1780	1.471
1781	1.215
1782	1.333
1783	1.294
1784	1.552
1785	1.784
1786	1.514
1787	1.41
1788	1.674
1789	1.756
1790	1.241
1791	1.449
1792	1.384
1793	1.389
1794	1.457
1795	1.24
1796	1.07
1797	0.858
1798	1.438
1799	1.237
1800	0.952
1801	1.305
1802	1.237
1803	1.353
1804	1.55
1805	1.393
1806	0.873
1807	1.131
1808	0.763
1809	0.875
1810	1.015
1811	1.106
1812	0.914
1813	0.907
1814	1.126
1815	1.279
1816	1.326
1817	1.404
1818	1.75
1819	1.663
1820	1.131
1821	0.912
1822	1.201
1823	1.211
1824	1.087
1825	1.184
1826	1.543
1827	1.261
1828	0.877
1829	0.997
1830	0.983
1831	1.162
1832	0.962
1833	1.042
1834	1.301
1835	0.951
1836	1.115
1837	0.85
1838	1.006
1839	1.094
1840	1.037
1841	0.751
1842	0.922
1843	1.016
1844	0.936
1845	1.007
1846	0.927
1847	0.683
1848	0.856
1849	1.059
1850	1.125
1851	1.256
1852	1.221
1853	1.127
1854	1.144
1855	1.132
1856	0.897
1857	0.926
1858	1.083
1859	0.873
1860	0.815
1861	1.02
1862	0.654
1863	0.675
1864	0.79
1865	0.92
1866	0.9
1867	0.841
1868	0.974
1869	0.805
1870	0.894
1871	0.998
1872	1.034
1873	1.164
1874	0.962
1875	1.049
1876	1.118
1877	1.103
1878	0.973
1879	1.016
1880	0.487
1881	0.537
1882	0.863
1883	0.96
1884	0.841
1885	0.913
1886	1.103
1887	1.181
1888	0.858
1889	1.006
1890	1.138
1891	0.844
1892	0.701
1893	0.629
1894	0.809
1895	0.934
1896	1.014
1897	0.782
1898	0.867
1899	0.75
1900	0.634
1901	1.056
1902	0.639
1903	0.586
1904	0.622
1905	0.622
1906	0.674
1907	0.748
1908	0.913
1909	0.989
1910	0.805
1911	0.905
1912	0.832
1913	0.794
1914	0.88
1915	1.173
1916	1.193
1917	1.04
1918	0.754
1919	0.734
1920	0.829
1921	1.138
1922	1.4
1923	1.332
1924	1.039
1925	1.241
1926	0.758
1927	0.815
1928	0.655
1929	0.745
1930	0.989
1931	0.829
1932	0.847
1933	0.711
1934	1.021
1935	0.876
1936	0.783
1937	0.932
1938	0.977
1939	0.679
1940	0.754
1941	1.018
1942	0.844
1943	1.01
1944	0.789
1945	0.518
1946	0.519
1947	1.113
1948	1.06
1949	1.063
1950	1.008
1951	0.789
1952	0.725
1953	1.0
1954	1.166
1955	0.83
1956	0.632
1957	1.005
1958	0.89
1959	1.025
1960	1.02
1961	0.847
1962	0.877
1963	0.784
1964	1.285
1965	1.072
1966	1.035
1967	0.995
1968	1.072
1969	1.024
1970	1.097
1971	0.814
1972	0.846
1973	1.123
1974	1.021
1975	1.058
1976	1.217
1977	1.042
1978	0.989
1979	1.204
1980	1.223
1981	0.994
1982	0.833
1983	1.012