# asia_russ157w - Taksimo dry - 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/4676
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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
#--------------------
# Title
#	Study_Name: asia_russ157w - Taksimo dry - 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: Taksimo dry
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 56.33
#	Southernmost_Latitude: 56.33
#	Easternmost_Longitude: 114.67
#	Westernmost_Longitude: 114.67
#	Elevation: 510 m
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# Data_Collection
#	Collection_Name: asia_russ157wB
#	Earliest_Year: 1736
#	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":"4.90292237485","T2":"14.9886049163","M1":"0.0227518495101","M2":"0.513612593564"}}
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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
1736	1.058
1737	1.098
1738	0.942
1739	0.974
1740	1.118
1741	1.045
1742	0.95
1743	0.996
1744	1.021
1745	1.098
1746	0.788
1747	0.98
1748	1.098
1749	1.074
1750	0.814
1751	0.856
1752	0.974
1753	1.208
1754	0.951
1755	0.873
1756	0.936
1757	0.917
1758	0.894
1759	0.964
1760	1.257
1761	1.164
1762	1.019
1763	1.13
1764	1.165
1765	1.104
1766	0.949
1767	0.859
1768	0.994
1769	1.125
1770	1.131
1771	0.967
1772	1.088
1773	1.266
1774	0.941
1775	1.09
1776	1.188
1777	0.887
1778	0.903
1779	1.033
1780	0.96
1781	0.957
1782	0.833
1783	0.818
1784	0.593
1785	0.695
1786	0.743
1787	0.82
1788	0.781
1789	0.918
1790	0.694
1791	0.861
1792	1.013
1793	1.033
1794	0.698
1795	0.842
1796	1.009
1797	0.984
1798	1.113
1799	1.122
1800	1.116
1801	1.206
1802	1.215
1803	1.192
1804	0.81
1805	1.04
1806	1.01
1807	0.925
1808	1.201
1809	1.038
1810	1.143
1811	0.971
1812	0.895
1813	1.048
1814	1.088
1815	1.108
1816	1.132
1817	0.754
1818	0.991
1819	1.011
1820	0.986
1821	0.93
1822	1.033
1823	0.957
1824	0.999
1825	1.001
1826	0.994
1827	1.194
1828	1.179
1829	1.164
1830	1.269
1831	1.239
1832	1.075
1833	0.917
1834	0.801
1835	0.902
1836	0.82
1837	0.827
1838	0.599
1839	0.816
1840	0.773
1841	0.888
1842	0.894
1843	0.995
1844	0.968
1845	0.854
1846	0.854
1847	0.493
1848	0.775
1849	0.934
1850	0.985
1851	1.206
1852	0.949
1853	0.86
1854	1.072
1855	1.05
1856	1.363
1857	1.067
1858	1.046
1859	1.108
1860	0.555
1861	1.156
1862	0.9
1863	1.18
1864	0.916
1865	0.872
1866	1.032
1867	1.127
1868	0.914
1869	0.944
1870	1.031
1871	1.109
1872	1.389
1873	1.476
1874	1.242
1875	0.996
1876	1.124
1877	1.021
1878	1.042
1879	1.104
1880	1.068
1881	0.931
1882	1.029
1883	1.302
1884	1.248
1885	1.217
1886	1.194
1887	0.923
1888	0.857
1889	0.928
1890	0.616
1891	0.914
1892	0.714
1893	0.925
1894	0.996
1895	0.839
1896	0.835
1897	0.877
1898	0.878
1899	0.98
1900	1.135
1901	0.81
1902	0.556
1903	0.707
1904	0.812
1905	0.952
1906	0.987
1907	0.801
1908	0.865
1909	0.91
1910	0.522
1911	0.791
1912	0.855
1913	0.833
1914	1.082
1915	0.937
1916	0.811
1917	0.769
1918	1.122
1919	0.848
1920	1.03
1921	1.286
1922	0.885
1923	1.065
1924	0.719
1925	1.112
1926	1.479
1927	1.21
1928	1.047
1929	1.399
1930	1.194
1931	1.158
1932	1.214
1933	1.299
1934	1.19
1935	1.29
1936	1.116
1937	1.325
1938	1.143
1939	0.641
1940	0.744
1941	0.844
1942	1.044
1943	0.647
1944	1.028
1945	0.669
1946	0.884
1947	0.874
1948	0.957
1949	1.09
1950	1.228
1951	1.222
1952	1.493
1953	1.339
1954	1.282
1955	1.176
1956	1.187
1957	1.119
1958	0.963
1959	1.131
1960	0.831
1961	1.234
1962	1.402
1963	1.144
1964	1.099
1965	0.979
1966	1.084
1967	0.905
1968	0.991
1969	0.846
1970	0.993
1971	0.964
1972	0.874
1973	0.783
1974	0.877
1975	0.876
1976	0.976
1977	0.9
1978	0.974
1979	0.977
1980	0.988
1981	0.932
1982	1.082
1983	1.138
1984	0.967
1985	0.7
1986	0.893
1987	0.471
1988	0.513
1989	0.936
1990	0.819
1991	0.909
1992	0.907
1993	1.2
1994	1.094
1995	0.961
1996	1.221