# europe_swed325 - TannsjÃÂ¶ - 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/6141
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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_swed325 - TannsjÃÂ¶ - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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: TannsjÃÂ¶
#	Location:
#	Country: Sweden
#	Northernmost_Latitude: 63.98
#	Southernmost_Latitude: 63.98
#	Easternmost_Longitude: 16.53
#	Westernmost_Longitude: 16.53
#	Elevation: 270 m
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# Data_Collection
#	Collection_Name: europe_swed325B
#	Earliest_Year: 1702
#	Most_Recent_Year: 1999
#	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":"4.66956763741","T2":"17.0144655534","M1":"0.0224033400073","M2":"0.452154232978"}}
#--------------------
# 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
#
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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
1702	1.335
1703	1.3
1704	1.004
1705	1.032
1706	0.875
1707	1.04
1708	0.743
1709	0.778
1710	0.995
1711	1.022
1712	1.006
1713	0.827
1714	1.089
1715	1.01
1716	1.224
1717	1.193
1718	1.146
1719	1.064
1720	1.146
1721	0.992
1722	1.099
1723	1.262
1724	1.149
1725	1.136
1726	1.127
1727	1.057
1728	0.862
1729	0.998
1730	1.104
1731	1.004
1732	1.109
1733	0.949
1734	0.893
1735	0.706
1736	0.776
1737	0.862
1738	1.078
1739	1.05
1740	0.927
1741	0.733
1742	0.832
1743	0.837
1744	0.922
1745	0.789
1746	0.757
1747	0.814
1748	0.931
1749	0.838
1750	0.947
1751	1.134
1752	1.511
1753	1.096
1754	1.166
1755	1.253
1756	0.943
1757	0.959
1758	0.964
1759	1.079
1760	1.002
1761	0.994
1762	1.179
1763	1.321
1764	1.314
1765	1.14
1766	1.312
1767	0.974
1768	0.999
1769	0.938
1770	0.814
1771	0.82
1772	0.829
1773	0.773
1774	0.925
1775	0.895
1776	0.818
1777	0.937
1778	1.1
1779	1.043
1780	0.83
1781	0.833
1782	0.793
1783	0.767
1784	1.097
1785	1.082
1786	0.807
1787	0.829
1788	0.912
1789	0.819
1790	0.55
1791	0.804
1792	0.747
1793	0.715
1794	0.778
1795	0.667
1796	0.633
1797	0.59
1798	0.701
1799	0.914
1800	0.791
1801	0.874
1802	0.837
1803	0.803
1804	0.96
1805	0.986
1806	0.864
1807	0.846
1808	0.723
1809	0.785
1810	0.659
1811	0.848
1812	0.718
1813	0.745
1814	0.842
1815	0.893
1816	1.136
1817	1.245
1818	1.388
1819	1.636
1820	1.211
1821	1.043
1822	1.201
1823	1.262
1824	0.986
1825	1.247
1826	1.657
1827	1.459
1828	1.561
1829	1.265
1830	1.128
1831	1.142
1832	0.806
1833	1.035
1834	1.053
1835	0.647
1836	0.802
1837	0.742
1838	0.833
1839	0.686
1840	0.61
1841	0.709
1842	0.607
1843	0.426
1844	0.372
1845	0.564
1846	0.581
1847	0.512
1848	0.627
1849	0.486
1850	0.523
1851	0.742
1852	0.724
1853	0.679
1854	1.105
1855	1.064
1856	0.974
1857	1.05
1858	1.452
1859	1.128
1860	1.35
1861	1.583
1862	1.15
1863	1.38
1864	1.466
1865	1.121
1866	1.486
1867	1.303
1868	1.67
1869	1.516
1870	1.559
1871	1.502
1872	1.476
1873	1.394
1874	1.406
1875	1.425
1876	1.406
1877	1.369
1878	1.219
1879	1.14
1880	1.019
1881	0.839
1882	1.363
1883	1.093
1884	1.254
1885	1.353
1886	1.023
1887	1.058
1888	0.871
1889	1.046
1890	1.138
1891	1.32
1892	1.11
1893	1.061
1894	1.167
1895	1.068
1896	1.219
1897	1.041
1898	1.124
1899	1.105
1900	1.128
1901	1.358
1902	0.883
1903	0.799
1904	0.752
1905	0.95
1906	1.02
1907	0.91
1908	1.031
1909	0.891
1910	0.833
1911	0.672
1912	0.787
1913	0.791
1914	1.212
1915	1.295
1916	1.214
1917	1.107
1918	1.143
1919	0.985
1920	0.953
1921	1.024
1922	1.413
1923	1.382
1924	1.231
1925	1.407
1926	0.939
1927	1.06
1928	0.791
1929	1.128
1930	1.316
1931	0.957
1932	0.999
1933	1.143
1934	1.173
1935	0.809
1936	0.765
1937	0.848
1938	0.749
1939	1.048
1940	1.004
1941	1.089
1942	0.877
1943	1.125
1944	1.121
1945	1.001
1946	1.087
1947	1.239
1948	1.113
1949	1.151
1950	1.103
1951	0.998
1952	0.897
1953	1.221
1954	1.272
1955	1.187
1956	0.975
1957	0.965
1958	0.998
1959	1.012
1960	1.028
1961	0.664
1962	0.78
1963	0.825
1964	0.833
1965	0.783
1966	0.75
1967	0.863
1968	0.821
1969	0.592
1970	0.699
1971	0.723
1972	0.821
1973	0.996
1974	0.871
1975	0.91
1976	0.747
1977	0.651
1978	0.777
1979	0.82
1980	0.751
1981	0.515
1982	0.526
1983	0.596
1984	0.629
1985	0.937
1986	0.887
1987	0.77
1988	0.871
1989	1.008
1990	0.94
1991	1.021
1992	0.996
1993	0.684
1994	0.792
1995	0.712
1996	0.7
1997	0.829
1998	0.736
1999	0.439