# asia_russ041w - Nonburg - 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/4563
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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
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# Title
#	Study_Name: asia_russ041w - Nonburg - 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: Nonburg
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 65.6
#	Southernmost_Latitude: 65.6
#	Easternmost_Longitude: 50.63
#	Westernmost_Longitude: 50.63
#	Elevation: 70 m
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# Data_Collection
#	Collection_Name: asia_russ041wB
#	Earliest_Year: 1723
#	Most_Recent_Year: 1990
#	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":"6.24577086109","T2":"19.6794589101","M1":"0.0221778085714","M2":"0.261174487783"}}
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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)
#
##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
1723	0.77
1724	0.811
1725	1.164
1726	1.209
1727	1.0
1728	0.931
1729	0.991
1730	0.794
1731	0.689
1732	0.621
1733	0.7
1734	0.618
1735	0.692
1736	0.773
1737	0.696
1738	0.898
1739	0.905
1740	0.721
1741	1.036
1742	0.914
1743	1.036
1744	1.074
1745	1.185
1746	0.901
1747	0.967
1748	0.839
1749	0.855
1750	1.122
1751	0.915
1752	0.676
1753	0.894
1754	1.131
1755	1.283
1756	1.327
1757	1.273
1758	1.43
1759	1.151
1760	1.085
1761	1.115
1762	1.178
1763	0.974
1764	0.984
1765	1.002
1766	0.88
1767	1.231
1768	1.182
1769	0.953
1770	0.719
1771	1.32
1772	0.893
1773	1.082
1774	1.452
1775	1.403
1776	0.913
1777	0.967
1778	0.93
1779	0.789
1780	1.023
1781	0.889
1782	0.992
1783	0.883
1784	0.848
1785	1.032
1786	0.755
1787	0.716
1788	0.907
1789	0.839
1790	1.028
1791	1.124
1792	1.241
1793	1.464
1794	1.161
1795	1.207
1796	1.198
1797	0.94
1798	0.878
1799	0.801
1800	1.082
1801	0.94
1802	1.224
1803	1.031
1804	0.949
1805	1.118
1806	0.92
1807	0.992
1808	0.976
1809	0.901
1810	0.5
1811	0.691
1812	0.883
1813	0.668
1814	0.61
1815	0.574
1816	0.431
1817	0.202
1818	0.488
1819	0.642
1820	0.577
1821	0.753
1822	0.721
1823	0.748
1824	0.791
1825	0.771
1826	0.824
1827	1.081
1828	0.843
1829	1.21
1830	1.417
1831	1.348
1832	1.665
1833	1.439
1834	1.162
1835	0.894
1836	0.874
1837	0.629
1838	0.456
1839	0.808
1840	1.034
1841	0.915
1842	1.221
1843	0.951
1844	1.408
1845	0.938
1846	0.974
1847	0.968
1848	0.965
1849	1.171
1850	1.236
1851	1.29
1852	1.179
1853	1.103
1854	0.989
1855	0.917
1856	1.031
1857	0.788
1858	0.461
1859	0.87
1860	0.853
1861	0.682
1862	0.49
1863	0.257
1864	0.963
1865	0.512
1866	0.584
1867	0.443
1868	0.315
1869	0.62
1870	0.731
1871	0.55
1872	0.57
1873	0.526
1874	0.664
1875	0.557
1876	0.671
1877	0.836
1878	1.124
1879	1.063
1880	0.963
1881	0.79
1882	0.696
1883	0.871
1884	1.078
1885	1.19
1886	0.856
1887	0.676
1888	0.538
1889	0.564
1890	0.893
1891	0.897
1892	0.491
1893	1.172
1894	0.833
1895	0.656
1896	0.956
1897	0.942
1898	1.373
1899	0.96
1900	1.119
1901	1.124
1902	1.312
1903	0.396
1904	1.015
1905	1.444
1906	1.624
1907	1.617
1908	1.584
1909	1.592
1910	1.384
1911	1.522
1912	1.511
1913	1.734
1914	1.209
1915	1.537
1916	1.34
1917	1.323
1918	1.213
1919	1.106
1920	1.075
1921	1.142
1922	1.383
1923	1.524
1924	1.607
1925	2.032
1926	1.3
1927	1.467
1928	1.375
1929	0.995
1930	0.955
1931	0.811
1932	0.964
1933	1.208
1934	1.328
1935	1.238
1936	1.343
1937	1.393
1938	1.236
1939	1.271
1940	1.572
1941	0.802
1942	0.881
1943	0.963
1944	0.942
1945	0.873
1946	0.741
1947	0.655
1948	0.909
1949	1.082
1950	1.147
1951	1.196
1952	1.259
1953	0.899
1954	1.366
1955	1.141
1956	1.304
1957	1.526
1958	0.872
1959	0.813
1960	1.034
1961	0.933
1962	0.651
1963	0.654
1964	0.926
1965	1.003
1966	1.016
1967	0.988
1968	0.849
1969	0.448
1970	0.755
1971	0.727
1972	0.73
1973	0.679
1974	0.855
1975	0.552
1976	0.783
1977	0.864
1978	0.838
1979	0.76
1980	0.702
1981	0.894
1982	0.517
1983	0.752
1984	1.072
1985	0.626
1986	0.578
1987	0.651
1988	0.974
1989	0.967
1990	0.881