# asia_russ170w - Severobaikalsk, trocken - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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/4635
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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: asia_russ170w - Severobaikalsk, trocken - 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: Severobaikalsk, trocken
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 55.25
#	Southernmost_Latitude: 55.25
#	Easternmost_Longitude: 109.5
#	Westernmost_Longitude: 109.5
#	Elevation: 540 m
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# Data_Collection
#	Collection_Name: asia_russ170wB
#	Earliest_Year: 1758
#	Most_Recent_Year: 1996
#	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":"3.29582236999","T2":"14.981125703","M1":"0.0240021797029","M2":"0.519551581555"}}
#--------------------
# 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
1758	0.375
1759	1.031
1760	1.166
1761	1.242
1762	0.731
1763	1.181
1764	0.785
1765	0.85
1766	0.507
1767	1.251
1768	1.231
1769	1.002
1770	0.774
1771	1.101
1772	1.084
1773	1.055
1774	1.503
1775	1.512
1776	1.306
1777	1.579
1778	1.6
1779	1.422
1780	1.169
1781	0.892
1782	0.788
1783	1.126
1784	0.822
1785	1.204
1786	1.037
1787	0.576
1788	0.565
1789	1.012
1790	0.965
1791	0.751
1792	1.257
1793	1.267
1794	0.93
1795	1.377
1796	0.892
1797	0.846
1798	0.551
1799	0.527
1800	1.108
1801	0.878
1802	1.228
1803	1.03
1804	0.567
1805	0.42
1806	0.55
1807	0.614
1808	1.012
1809	1.03
1810	1.064
1811	0.402
1812	0.409
1813	0.85
1814	0.623
1815	1.059
1816	0.941
1817	1.209
1818	1.048
1819	1.594
1820	1.113
1821	1.353
1822	1.136
1823	1.322
1824	1.291
1825	1.255
1826	1.716
1827	1.891
1828	1.727
1829	0.654
1830	1.569
1831	0.953
1832	1.351
1833	1.214
1834	0.393
1835	1.183
1836	0.861
1837	0.454
1838	0.51
1839	0.706
1840	0.95
1841	0.904
1842	0.611
1843	0.873
1844	0.907
1845	1.016
1846	1.02
1847	0.511
1848	0.773
1849	0.54
1850	0.944
1851	0.821
1852	0.406
1853	0.968
1854	1.102
1855	1.213
1856	1.062
1857	1.262
1858	0.943
1859	1.478
1860	1.229
1861	1.003
1862	1.218
1863	0.629
1864	0.942
1865	1.291
1866	1.281
1867	1.552
1868	1.04
1869	1.287
1870	1.22
1871	1.52
1872	1.104
1873	1.05
1874	0.846
1875	1.136
1876	1.254
1877	1.133
1878	0.503
1879	0.647
1880	0.622
1881	0.967
1882	1.02
1883	1.617
1884	0.917
1885	1.419
1886	1.439
1887	0.705
1888	1.014
1889	0.572
1890	0.703
1891	1.335
1892	0.609
1893	0.827
1894	0.84
1895	0.547
1896	0.489
1897	0.489
1898	0.419
1899	0.536
1900	0.602
1901	0.496
1902	0.571
1903	0.193
1904	0.671
1905	0.767
1906	0.952
1907	1.247
1908	0.903
1909	1.479
1910	0.836
1911	0.421
1912	0.985
1913	0.821
1914	1.386
1915	1.292
1916	0.674
1917	0.256
1918	0.672
1919	0.704
1920	0.952
1921	0.789
1922	0.515
1923	0.884
1924	0.925
1925	1.409
1926	1.557
1927	1.202
1928	1.395
1929	1.543
1930	1.5
1931	1.408
1932	1.216
1933	1.199
1934	0.67
1935	1.576
1936	1.328
1937	0.849
1938	1.714
1939	1.131
1940	0.737
1941	0.744
1942	1.274
1943	0.617
1944	0.556
1945	0.395
1946	1.142
1947	1.037
1948	1.627
1949	2.317
1950	1.746
1951	1.348
1952	1.335
1953	0.983
1954	0.65
1955	1.109
1956	1.057
1957	0.254
1958	0.847
1959	0.895
1960	0.819
1961	1.2
1962	1.081
1963	0.571
1964	0.621
1965	1.021
1966	1.111
1967	1.232
1968	1.149
1969	1.344
1970	1.289
1971	1.234
1972	1.365
1973	0.963
1974	1.163
1975	1.242
1976	1.165
1977	0.716
1978	0.929
1979	0.688
1980	0.554
1981	0.558
1982	0.515
1983	0.921
1984	0.737
1985	0.505
1986	1.016
1987	0.432
1988	0.845
1989	1.203
1990	0.622
1991	1.04
1992	0.889
1993	1.04
1994	0.593
1995	1.388
1996	1.798