# asia_russ174w - White River, P.Tung. - 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/4734
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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_russ174w - White River, P.Tung. - 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: White River, P.Tung.
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 61.85
#	Southernmost_Latitude: 61.85
#	Easternmost_Longitude: 93.4
#	Westernmost_Longitude: 93.4
#	Elevation: 120 m
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# Data_Collection
#	Collection_Name: asia_russ174wB
#	Earliest_Year: 1793
#	Most_Recent_Year: 1994
#	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":"4.85394069435","T2":"17.0381058735","M1":"0.0222495047384","M2":"0.499239786413"}}
#--------------------
# 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)
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##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
1793	0.754
1794	0.869
1795	0.75
1796	0.696
1797	0.448
1798	0.438
1799	0.664
1800	0.567
1801	0.515
1802	0.597
1803	0.71
1804	0.614
1805	0.67
1806	0.887
1807	0.843
1808	0.868
1809	0.823
1810	0.884
1811	1.254
1812	0.582
1813	0.82
1814	0.815
1815	0.656
1816	0.641
1817	0.62
1818	0.697
1819	0.777
1820	0.631
1821	0.698
1822	0.564
1823	0.138
1824	0.285
1825	0.357
1826	0.366
1827	0.445
1828	0.536
1829	0.646
1830	0.693
1831	0.804
1832	0.824
1833	1.106
1834	1.186
1835	1.315
1836	1.244
1837	1.344
1838	1.643
1839	1.41
1840	1.441
1841	1.323
1842	1.539
1843	1.215
1844	1.364
1845	1.335
1846	1.313
1847	1.359
1848	1.462
1849	1.372
1850	1.404
1851	1.112
1852	1.207
1853	1.37
1854	0.772
1855	1.476
1856	1.637
1857	1.385
1858	1.236
1859	1.219
1860	1.465
1861	1.568
1862	1.296
1863	1.481
1864	1.322
1865	1.518
1866	1.491
1867	1.042
1868	1.279
1869	1.007
1870	1.093
1871	0.996
1872	1.199
1873	1.114
1874	1.106
1875	1.143
1876	1.256
1877	1.212
1878	1.645
1879	1.161
1880	1.172
1881	0.75
1882	1.104
1883	0.791
1884	0.94
1885	0.888
1886	0.86
1887	0.816
1888	0.711
1889	0.571
1890	0.608
1891	0.858
1892	0.895
1893	1.07
1894	0.98
1895	0.714
1896	0.845
1897	0.732
1898	0.861
1899	0.725
1900	0.998
1901	0.673
1902	0.696
1903	0.957
1904	0.963
1905	0.905
1906	1.146
1907	0.675
1908	1.201
1909	0.467
1910	0.947
1911	0.791
1912	1.045
1913	0.899
1914	0.908
1915	0.76
1916	0.859
1917	0.692
1918	0.941
1919	0.544
1920	1.12
1921	0.676
1922	0.72
1923	0.725
1924	0.587
1925	0.729
1926	0.763
1927	1.032
1928	1.127
1929	0.674
1930	1.01
1931	0.953
1932	0.814
1933	0.759
1934	0.787
1935	0.848
1936	0.887
1937	0.801
1938	0.903
1939	0.994
1940	1.044
1941	0.945
1942	1.125
1943	1.007
1944	1.031
1945	1.044
1946	1.255
1947	1.209
1948	1.33
1949	0.95
1950	1.215
1951	0.913
1952	1.095
1953	1.126
1954	1.126
1955	0.918
1956	0.959
1957	1.023
1958	0.914
1959	0.892
1960	0.824
1961	0.735
1962	1.08
1963	0.805
1964	0.996
1965	0.883
1966	0.88
1967	0.924
1968	1.025
1969	0.968
1970	0.714
1971	0.952
1972	1.013
1973	0.923
1974	0.898
1975	1.039
1976	1.113
1977	1.16
1978	1.032
1979	1.293
1980	0.978
1981	1.037
1982	0.986
1983	1.094
1984	1.026
1985	1.196
1986	1.057
1987	0.775
1988	0.996
1989	1.034
1990	1.201
1991	1.242
1992	1.134
1993	1.343
1994	1.216