# europe_swed324 - Skuleskogen - Breitenmoser Tree Ring Chronology Data
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#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
#-----------------------------------------------------------------------
# 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/6138
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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_swed324 - Skuleskogen - 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: Skuleskogen
#	Location:
#	Country: Sweden
#	Northernmost_Latitude: 62.33
#	Southernmost_Latitude: 62.33
#	Easternmost_Longitude: 18.48
#	Westernmost_Longitude: 18.48
#	Elevation: 250 m
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# Data_Collection
#	Collection_Name: europe_swed324B
#	Earliest_Year: 1700
#	Most_Recent_Year: 1998
#	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":"3.83046711509","T2":"13.9318919856","M1":"0.0227576812114","M2":"0.538183493094"}}
#--------------------
# 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
1700	1.202
1701	0.966
1702	0.922
1703	1.125
1704	0.675
1705	0.687
1706	0.827
1707	0.751
1708	0.922
1709	0.902
1710	1.195
1711	0.815
1712	1.328
1713	1.08
1714	1.403
1715	1.678
1716	1.054
1717	1.128
1718	1.12
1719	0.943
1720	1.161
1721	1.074
1722	1.18
1723	1.155
1724	1.152
1725	1.055
1726	0.602
1727	0.81
1728	0.738
1729	0.8
1730	0.915
1731	1.42
1732	1.026
1733	1.069
1734	1.097
1735	0.856
1736	0.806
1737	0.755
1738	0.872
1739	0.734
1740	0.476
1741	0.347
1742	0.485
1743	0.754
1744	0.935
1745	0.717
1746	0.774
1747	0.681
1748	0.882
1749	0.67
1750	0.87
1751	0.978
1752	1.324
1753	1.124
1754	1.091
1755	1.023
1756	1.017
1757	1.303
1758	1.207
1759	0.946
1760	0.915
1761	1.068
1762	1.801
1763	1.423
1764	1.113
1765	0.958
1766	0.931
1767	0.796
1768	0.63
1769	0.745
1770	0.767
1771	0.584
1772	0.695
1773	0.708
1774	0.646
1775	1.447
1776	1.547
1777	1.73
1778	1.616
1779	1.442
1780	1.105
1781	0.481
1782	0.729
1783	0.688
1784	0.99
1785	0.856
1786	0.736
1787	0.867
1788	0.772
1789	0.912
1790	0.549
1791	0.812
1792	1.022
1793	1.284
1794	1.1
1795	0.56
1796	0.92
1797	0.981
1798	0.872
1799	1.272
1800	1.066
1801	1.133
1802	0.966
1803	0.845
1804	1.233
1805	1.702
1806	1.391
1807	1.095
1808	0.871
1809	1.055
1810	0.837
1811	0.98
1812	1.199
1813	0.864
1814	1.074
1815	1.004
1816	0.855
1817	1.185
1818	1.195
1819	1.199
1820	0.998
1821	0.859
1822	0.548
1823	0.889
1824	0.802
1825	1.018
1826	1.087
1827	1.271
1828	1.314
1829	1.195
1830	1.019
1831	0.514
1832	0.319
1833	0.669
1834	0.498
1835	0.409
1836	0.722
1837	0.71
1838	0.872
1839	0.681
1840	0.684
1841	0.496
1842	0.639
1843	0.771
1844	0.768
1845	0.797
1846	0.89
1847	0.539
1848	0.594
1849	0.658
1850	0.915
1851	0.951
1852	0.788
1853	0.475
1854	0.769
1855	0.965
1856	1.103
1857	1.208
1858	1.18
1859	0.835
1860	1.066
1861	0.515
1862	0.55
1863	0.722
1864	0.851
1865	0.956
1866	1.166
1867	0.864
1868	1.214
1869	0.92
1870	0.958
1871	0.735
1872	0.762
1873	0.806
1874	0.55
1875	0.86
1876	0.935
1877	1.068
1878	0.994
1879	0.91
1880	0.715
1881	0.705
1882	1.069
1883	0.886
1884	0.928
1885	0.966
1886	0.986
1887	0.856
1888	0.766
1889	1.228
1890	1.244
1891	0.745
1892	0.993
1893	0.871
1894	0.764
1895	0.805
1896	1.127
1897	0.809
1898	0.849
1899	0.774
1900	0.828
1901	1.14
1902	0.746
1903	0.744
1904	0.921
1905	1.142
1906	1.019
1907	1.155
1908	0.97
1909	0.818
1910	0.892
1911	0.957
1912	1.046
1913	1.161
1914	1.003
1915	1.112
1916	1.027
1917	1.034
1918	1.198
1919	1.367
1920	1.079
1921	1.406
1922	1.789
1923	1.404
1924	1.567
1925	1.52
1926	1.117
1927	1.052
1928	1.139
1929	1.524
1930	1.045
1931	0.867
1932	0.968
1933	0.703
1934	0.73
1935	0.718
1936	0.675
1937	1.002
1938	0.798
1939	0.846
1940	0.596
1941	0.989
1942	0.943
1943	0.908
1944	1.31
1945	1.235
1946	1.344
1947	1.496
1948	1.138
1949	1.157
1950	1.188
1951	1.204
1952	1.343
1953	1.534
1954	1.692
1955	0.949
1956	1.277
1957	1.54
1958	1.361
1959	0.84
1960	0.821
1961	0.805
1962	1.245
1963	0.933
1964	1.186
1965	1.109
1966	0.809
1967	1.077
1968	0.767
1969	0.438
1970	0.822
1971	1.051
1972	1.365
1973	0.977
1974	1.201
1975	1.187
1976	1.04
1977	0.961
1978	1.039
1979	1.171
1980	1.264
1981	1.017
1982	1.135
1983	1.226
1984	1.287
1985	1.192
1986	1.031
1987	1.23
1988	0.942
1989	0.876
1990	1.211
1991	1.368
1992	0.587
1993	0.76
1994	0.89
1995	0.765
1996	0.914
1997	0.697
1998	0.828