# asia_russ027w - Indikyakha-River - 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/4438
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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_russ027w - Indikyakha-River - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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: Indikyakha-River
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 68.25
#	Southernmost_Latitude: 68.25
#	Easternmost_Longitude: 80.18
#	Westernmost_Longitude: 80.18
#	Elevation: 60 m
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# Data_Collection
#	Collection_Name: asia_russ027wB
#	Earliest_Year: 1705
#	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":"7.60191730896","T2":"18.6875680756","M1":"0.0223466975859","M2":"0.350318973815"}}
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# Species
#	Species_Name: Siberian larch
#	Species_Code: LASI
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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
1705	1.15
1706	0.78
1707	1.73
1708	1.345
1709	1.846
1710	1.397
1711	1.097
1712	1.189
1713	0.997
1714	0.368
1715	1.401
1716	1.128
1717	0.711
1718	0.554
1719	1.143
1720	0.96
1721	1.029
1722	1.111
1723	1.093
1724	1.687
1725	0.782
1726	1.256
1727	1.191
1728	0.741
1729	1.02
1730	0.764
1731	1.046
1732	0.265
1733	1.21
1734	0.66
1735	1.115
1736	0.465
1737	0.827
1738	0.634
1739	0.604
1740	0.833
1741	0.717
1742	0.227
1743	1.05
1744	0.957
1745	0.692
1746	0.906
1747	0.654
1748	0.555
1749	0.516
1750	0.659
1751	1.06
1752	0.712
1753	0.812
1754	1.276
1755	0.927
1756	1.157
1757	1.424
1758	0.738
1759	0.509
1760	1.32
1761	1.573
1762	1.731
1763	1.587
1764	1.123
1765	1.144
1766	1.208
1767	1.452
1768	0.693
1769	0.962
1770	0.619
1771	1.041
1772	0.381
1773	0.657
1774	0.512
1775	1.495
1776	0.595
1777	1.096
1778	1.647
1779	1.429
1780	1.188
1781	1.056
1782	1.348
1783	0.171
1784	1.278
1785	1.206
1786	1.069
1787	1.242
1788	0.588
1789	0.833
1790	1.308
1791	1.145
1792	1.176
1793	2.237
1794	2.015
1795	1.39
1796	1.57
1797	1.131
1798	1.193
1799	1.021
1800	0.742
1801	1.252
1802	0.881
1803	0.935
1804	0.819
1805	1.435
1806	1.085
1807	0.877
1808	1.318
1809	1.381
1810	1.046
1811	1.089
1812	0.416
1813	0.81
1814	0.908
1815	0.538
1816	0.526
1817	0.864
1818	0.849
1819	0.363
1820	0.49
1821	0.777
1822	1.055
1823	0.833
1824	0.696
1825	0.204
1826	0.717
1827	0.971
1828	0.581
1829	1.138
1830	0.629
1831	0.587
1832	1.07
1833	0.116
1834	0.383
1835	0.558
1836	0.499
1837	0.455
1838	0.734
1839	1.009
1840	0.829
1841	0.326
1842	0.943
1843	0.59
1844	1.327
1845	1.696
1846	1.535
1847	1.204
1848	1.139
1849	1.011
1850	1.109
1851	1.184
1852	1.2
1853	1.36
1854	1.109
1855	0.636
1856	1.427
1857	1.279
1858	0.996
1859	1.216
1860	0.832
1861	1.468
1862	0.907
1863	0.739
1864	0.558
1865	0.75
1866	0.853
1867	0.109
1868	1.06
1869	0.56
1870	1.416
1871	0.905
1872	1.23
1873	0.765
1874	0.626
1875	0.866
1876	1.076
1877	1.341
1878	1.719
1879	1.543
1880	0.761
1881	0.5
1882	0.227
1883	0.83
1884	0.231
1885	0.221
1886	0.903
1887	0.893
1888	0.764
1889	0.28
1890	0.858
1891	0.364
1892	0.965
1893	0.486
1894	0.954
1895	0.992
1896	0.621
1897	1.325
1898	1.756
1899	0.347
1900	1.236
1901	0.51
1902	1.069
1903	0.711
1904	1.061
1905	1.173
1906	1.085
1907	0.439
1908	1.259
1909	1.427
1910	1.467
1911	1.184
1912	0.713
1913	0.648
1914	0.41
1915	1.076
1916	0.366
1917	0.757
1918	1.517
1919	0.985
1920	0.938
1921	1.075
1922	1.35
1923	1.753
1924	1.546
1925	1.058
1926	1.236
1927	0.799
1928	0.973
1929	1.302
1930	1.346
1931	0.838
1932	1.356
1933	1.418
1934	0.397
1935	0.7
1936	0.606
1937	0.767
1938	0.996
1939	0.945
1940	0.832
1941	0.839
1942	1.843
1943	1.652
1944	2.014
1945	2.283
1946	1.56
1947	0.625
1948	1.852
1949	0.893
1950	1.191
1951	1.254
1952	0.935
1953	1.289
1954	0.803
1955	1.645
1956	1.621
1957	1.202
1958	1.411
1959	1.599
1960	0.994
1961	1.304
1962	1.094
1963	1.144
1964	1.474
1965	1.425
1966	0.763
1967	1.243
1968	0.66
1969	1.257
1970	0.783
1971	0.409
1972	0.684
1973	0.352
1974	0.685
1975	0.448
1976	0.849
1977	0.652
1978	1.033
1979	1.111
1980	0.557
1981	0.812
1982	0.995
1983	0.905
1984	1.201
1985	0.96
1986	1.225
1987	1.199
1988	0.861
1989	0.816
1990	0.901