# asia_russ104w - Krasnovishersk - 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/4481
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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_russ104w - Krasnovishersk - Breitenmoser Tree Ring Chronology Data
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# 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: Krasnovishersk
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 60.38
#	Southernmost_Latitude: 60.38
#	Easternmost_Longitude: 57.12
#	Westernmost_Longitude: 57.12
#	Elevation: 140 m
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# Data_Collection
#	Collection_Name: asia_russ104wB
#	Earliest_Year: 1747
#	Most_Recent_Year: 1991
#	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":"4.06344045488","T2":"15.4447799543","M1":"0.0226098286039","M2":"0.523532259583"}}
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# Species
#	Species_Name: Siberian spruce
#	Species_Code: PCOB
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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
1747	0.862
1748	1.046
1749	0.919
1750	0.744
1751	0.807
1752	1.088
1753	1.099
1754	0.982
1755	0.994
1756	1.24
1757	1.019
1758	0.648
1759	0.602
1760	0.549
1761	0.676
1762	0.737
1763	0.739
1764	0.746
1765	0.854
1766	0.388
1767	0.661
1768	0.678
1769	0.872
1770	0.759
1771	0.776
1772	0.803
1773	0.787
1774	0.694
1775	0.519
1776	0.57
1777	0.729
1778	0.452
1779	0.684
1780	0.919
1781	1.258
1782	0.802
1783	0.588
1784	1.004
1785	0.759
1786	0.687
1787	0.69
1788	0.91
1789	0.541
1790	0.692
1791	0.46
1792	0.442
1793	0.579
1794	0.638
1795	0.595
1796	0.577
1797	0.511
1798	0.627
1799	0.529
1800	0.689
1801	0.749
1802	0.438
1803	0.449
1804	0.644
1805	0.813
1806	0.742
1807	0.81
1808	0.919
1809	0.996
1810	0.892
1811	1.033
1812	0.925
1813	0.908
1814	0.671
1815	0.683
1816	0.723
1817	0.809
1818	0.747
1819	0.79
1820	0.752
1821	0.663
1822	0.747
1823	0.898
1824	0.922
1825	0.741
1826	0.879
1827	0.834
1828	0.769
1829	0.864
1830	0.816
1831	0.61
1832	0.592
1833	0.753
1834	0.816
1835	0.763
1836	0.696
1837	0.722
1838	0.902
1839	0.985
1840	0.721
1841	0.806
1842	0.859
1843	0.924
1844	0.878
1845	0.888
1846	1.141
1847	1.132
1848	0.978
1849	1.135
1850	1.172
1851	1.08
1852	0.915
1853	0.93
1854	1.129
1855	1.381
1856	1.724
1857	1.507
1858	1.851
1859	2.128
1860	1.439
1861	1.435
1862	1.195
1863	1.456
1864	1.356
1865	1.321
1866	1.508
1867	1.541
1868	1.899
1869	1.713
1870	1.589
1871	1.522
1872	1.422
1873	1.058
1874	0.89
1875	1.109
1876	1.208
1877	1.15
1878	1.637
1879	1.613
1880	1.637
1881	1.32
1882	1.277
1883	1.105
1884	1.36
1885	1.235
1886	1.061
1887	1.019
1888	1.341
1889	1.621
1890	0.863
1891	0.984
1892	1.191
1893	0.885
1894	0.995
1895	0.961
1896	0.786
1897	0.919
1898	1.042
1899	0.816
1900	1.003
1901	1.1
1902	1.119
1903	1.207
1904	0.828
1905	0.892
1906	1.377
1907	1.222
1908	0.935
1909	1.075
1910	1.196
1911	0.932
1912	0.847
1913	0.937
1914	0.745
1915	0.822
1916	0.643
1917	0.849
1918	0.994
1919	1.002
1920	0.914
1921	0.88
1922	0.951
1923	0.748
1924	0.943
1925	0.921
1926	1.062
1927	1.269
1928	0.967
1929	1.007
1930	0.949
1931	0.998
1932	0.953
1933	0.715
1934	0.745
1935	0.728
1936	0.565
1937	0.625
1938	0.612
1939	0.754
1940	0.597
1941	0.485
1942	0.631
1943	0.493
1944	0.527
1945	0.608
1946	0.719
1947	0.596
1948	0.878
1949	0.919
1950	1.04
1951	0.988
1952	0.716
1953	0.742
1954	0.762
1955	0.669
1956	0.879
1957	0.96
1958	0.796
1959	1.062
1960	0.832
1961	0.583
1962	0.734
1963	0.653
1964	0.884
1965	0.848
1966	0.793
1967	0.756
1968	0.901
1969	1.042
1970	0.948
1971	1.036
1972	1.087
1973	0.905
1974	1.148
1975	0.755
1976	1.1
1977	0.961
1978	0.948
1979	1.59
1980	1.514
1981	1.498
1982	0.915
1983	1.169
1984	1.178
1985	1.015
1986	1.047
1987	1.158
1988	0.84
1989	0.758
1990	0.793
1991	0.933