# asia_russ078w - Kheta River - 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.
#
#
# 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/4465
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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_russ078w - Kheta River - 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.
#--------------------
#	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: Kheta River
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 69.12
#	Southernmost_Latitude: 69.12
#	Easternmost_Longitude: 84.5
#	Westernmost_Longitude: 84.5
#	Elevation: 80 m
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# Data_Collection
#	Collection_Name: asia_russ078wB
#	Earliest_Year: 1682
#	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":"8.13255142217","T2":"19.4924391498","M1":"0.0225080166593","M2":"0.319492054428"}}
#--------------------
# Species
#	Species_Name: Siberian larch
#	Species_Code: LASI
#--------------------
# Chronology:
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#
#
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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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1682	0.718
1683	0.611
1684	0.523
1685	0.413
1686	0.708
1687	0.871
1688	1.112
1689	0.975
1690	1.066
1691	0.69
1692	0.795
1693	0.945
1694	0.677
1695	1.572
1696	0.778
1697	0.687
1698	0.641
1699	0.276
1700	0.568
1701	0.567
1702	0.258
1703	0.638
1704	0.48
1705	1.017
1706	0.902
1707	1.185
1708	1.107
1709	1.469
1710	1.242
1711	1.248
1712	1.043
1713	0.991
1714	0.521
1715	1.055
1716	1.177
1717	1.144
1718	0.493
1719	1.107
1720	1.489
1721	1.511
1722	1.047
1723	1.112
1724	1.333
1725	0.917
1726	1.281
1727	1.087
1728	0.918
1729	1.731
1730	1.814
1731	1.69
1732	0.319
1733	1.17
1734	0.71
1735	1.051
1736	0.558
1737	0.886
1738	0.804
1739	1.031
1740	1.335
1741	1.447
1742	0.243
1743	1.318
1744	1.061
1745	0.409
1746	0.875
1747	1.434
1748	1.049
1749	1.004
1750	0.78
1751	1.213
1752	0.986
1753	1.245
1754	1.429
1755	1.155
1756	0.992
1757	1.287
1758	0.761
1759	0.39
1760	0.613
1761	1.204
1762	1.49
1763	1.832
1764	1.328
1765	1.53
1766	1.6
1767	1.825
1768	0.83
1769	1.313
1770	1.008
1771	1.082
1772	0.444
1773	0.654
1774	0.33
1775	1.157
1776	0.595
1777	1.103
1778	1.001
1779	1.249
1780	0.671
1781	1.111
1782	1.615
1783	0.257
1784	1.341
1785	1.24
1786	1.212
1787	1.135
1788	0.51
1789	0.844
1790	0.707
1791	0.676
1792	0.816
1793	1.485
1794	1.409
1795	1.03
1796	1.314
1797	0.746
1798	1.053
1799	1.031
1800	0.73
1801	1.129
1802	0.907
1803	0.898
1804	1.03
1805	1.497
1806	1.53
1807	0.476
1808	1.23
1809	1.364
1810	0.862
1811	0.988
1812	0.303
1813	0.943
1814	0.953
1815	0.575
1816	0.706
1817	0.951
1818	0.914
1819	0.24
1820	0.466
1821	0.921
1822	1.026
1823	0.841
1824	0.694
1825	0.139
1826	0.35
1827	0.872
1828	0.537
1829	0.774
1830	0.19
1831	0.499
1832	0.537
1833	0.103
1834	0.34
1835	0.479
1836	0.382
1837	0.221
1838	0.669
1839	0.687
1840	0.645
1841	0.436
1842	0.847
1843	0.426
1844	1.097
1845	1.182
1846	0.947
1847	0.715
1848	0.811
1849	0.963
1850	0.87
1851	0.9
1852	1.208
1853	1.224
1854	1.024
1855	0.626
1856	1.196
1857	1.059
1858	0.546
1859	0.817
1860	0.907
1861	1.403
1862	0.999
1863	0.923
1864	1.171
1865	1.167
1866	0.87
1867	0.129
1868	1.101
1869	0.368
1870	0.942
1871	0.703
1872	1.127
1873	0.628
1874	0.551
1875	0.958
1876	1.264
1877	1.532
1878	1.763
1879	1.664
1880	1.062
1881	0.799
1882	0.438
1883	0.999
1884	0.273
1885	0.237
1886	0.969
1887	0.943
1888	0.777
1889	0.408
1890	0.845
1891	0.763
1892	1.395
1893	0.871
1894	1.265
1895	0.951
1896	1.119
1897	1.673
1898	1.653
1899	0.634
1900	1.222
1901	0.634
1902	0.9
1903	1.049
1904	0.961
1905	1.312
1906	1.131
1907	0.489
1908	2.346
1909	2.004
1910	1.706
1911	1.447
1912	1.204
1913	0.771
1914	0.651
1915	1.239
1916	0.493
1917	0.724
1918	1.439
1919	0.975
1920	1.18
1921	1.16
1922	1.067
1923	1.483
1924	1.631
1925	0.989
1926	1.346
1927	0.875
1928	1.613
1929	1.242
1930	0.888
1931	0.567
1932	1.227
1933	0.787
1934	0.193
1935	0.433
1936	0.458
1937	0.661
1938	0.893
1939	0.893
1940	1.029
1941	0.873
1942	1.207
1943	1.471
1944	1.604
1945	1.988
1946	1.523
1947	0.503
1948	1.477
1949	0.59
1950	1.263
1951	1.002
1952	0.838
1953	1.409
1954	0.856
1955	1.397
1956	1.512
1957	1.445
1958	1.305
1959	1.526
1960	0.937
1961	1.165
1962	1.021
1963	1.138
1964	1.227
1965	1.253
1966	0.785
1967	1.315
1968	0.724
1969	1.298
1970	0.949
1971	0.429
1972	0.825
1973	0.557
1974	0.514
1975	0.491
1976	1.0
1977	0.841
1978	1.065
1979	1.072
1980	0.837
1981	0.574
1982	0.69
1983	0.816
1984	1.009
1985	0.569
1986	1.09
1987	0.9
1988	0.691
1989	0.497
1990	0.653