# asia_russ096w - Murmashi - 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/4546
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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_russ096w - Murmashi - 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: Murmashi
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 68.77
#	Southernmost_Latitude: 68.77
#	Easternmost_Longitude: 32.8
#	Westernmost_Longitude: 32.8
#	Elevation: 140 m
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# Data_Collection
#	Collection_Name: asia_russ096wB
#	Earliest_Year: 1711
#	Most_Recent_Year: 1992
#	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":"6.72434482968","T2":"19.315286354","M1":"0.0226192617202","M2":"0.260772789674"}}
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# Species
#	Species_Name: Norway spruce
#	Species_Code: PCAB
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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
1711	1.261
1712	0.576
1713	0.975
1714	0.713
1715	1.175
1716	1.477
1717	1.314
1718	1.324
1719	1.083
1720	1.167
1721	1.016
1722	1.011
1723	1.07
1724	1.029
1725	1.096
1726	0.932
1727	0.705
1728	0.688
1729	0.784
1730	0.754
1731	0.764
1732	0.899
1733	0.933
1734	0.524
1735	0.991
1736	0.71
1737	0.604
1738	0.785
1739	0.782
1740	0.802
1741	0.598
1742	0.753
1743	0.727
1744	0.841
1745	0.863
1746	0.91
1747	0.631
1748	0.671
1749	0.81
1750	0.846
1751	0.816
1752	0.867
1753	0.999
1754	1.455
1755	1.388
1756	1.439
1757	1.623
1758	1.49
1759	1.537
1760	1.22
1761	1.463
1762	1.338
1763	1.398
1764	1.102
1765	0.961
1766	0.819
1767	1.046
1768	1.049
1769	0.91
1770	1.019
1771	1.161
1772	0.949
1773	1.153
1774	1.042
1775	1.025
1776	0.861
1777	1.177
1778	0.929
1779	1.058
1780	1.275
1781	0.994
1782	1.476
1783	1.321
1784	1.003
1785	1.126
1786	0.911
1787	0.729
1788	0.902
1789	0.739
1790	0.395
1791	0.805
1792	0.816
1793	1.05
1794	0.724
1795	0.473
1796	0.289
1797	0.329
1798	0.497
1799	0.761
1800	0.935
1801	0.937
1802	1.039
1803	0.691
1804	0.927
1805	0.955
1806	0.525
1807	0.999
1808	0.939
1809	1.209
1810	0.713
1811	1.129
1812	0.845
1813	0.637
1814	0.579
1815	0.539
1816	0.65
1817	0.464
1818	1.006
1819	1.226
1820	0.858
1821	0.819
1822	0.885
1823	1.424
1824	1.259
1825	1.499
1826	2.146
1827	1.936
1828	1.651
1829	2.094
1830	1.767
1831	1.905
1832	1.198
1833	1.557
1834	1.06
1835	1.363
1836	0.679
1837	0.687
1838	0.882
1839	0.732
1840	0.619
1841	0.639
1842	0.618
1843	0.583
1844	0.706
1845	1.16
1846	0.873
1847	0.927
1848	0.585
1849	0.923
1850	0.827
1851	1.196
1852	1.114
1853	1.39
1854	1.019
1855	0.909
1856	1.241
1857	0.753
1858	1.181
1859	1.018
1860	1.005
1861	1.225
1862	0.773
1863	0.964
1864	0.853
1865	0.619
1866	0.666
1867	0.579
1868	0.48
1869	0.594
1870	0.623
1871	0.296
1872	0.437
1873	0.518
1874	0.237
1875	0.742
1876	0.858
1877	0.94
1878	0.84
1879	0.481
1880	0.783
1881	1.009
1882	0.585
1883	1.142
1884	0.983
1885	0.953
1886	0.959
1887	0.803
1888	0.964
1889	1.632
1890	1.795
1891	1.581
1892	1.06
1893	1.336
1894	1.04
1895	1.464
1896	1.772
1897	1.126
1898	1.222
1899	0.957
1900	0.653
1901	1.063
1902	0.755
1903	0.784
1904	1.064
1905	0.991
1906	0.863
1907	1.183
1908	0.76
1909	0.605
1910	0.206
1911	0.58
1912	0.332
1913	0.516
1914	0.768
1915	0.714
1916	0.827
1917	0.775
1918	0.64
1919	0.907
1920	0.484
1921	0.855
1922	1.129
1923	0.915
1924	0.881
1925	1.037
1926	0.889
1927	1.486
1928	0.782
1929	1.018
1930	1.177
1931	0.797
1932	1.043
1933	1.232
1934	0.689
1935	0.838
1936	1.412
1937	1.244
1938	1.254
1939	1.304
1940	1.211
1941	1.324
1942	1.181
1943	0.851
1944	0.782
1945	0.927
1946	0.904
1947	1.397
1948	0.92
1949	0.584
1950	0.923
1951	0.758
1952	1.286
1953	1.156
1954	1.053
1955	0.767
1956	1.149
1957	0.741
1958	0.941
1959	0.609
1960	0.782
1961	1.007
1962	0.683
1963	0.844
1964	1.13
1965	1.066
1966	1.033
1967	0.778
1968	0.875
1969	0.908
1970	1.216
1971	0.767
1972	1.182
1973	0.831
1974	0.751
1975	0.32
1976	0.788
1977	0.97
1978	1.057
1979	1.324
1980	1.22
1981	1.288
1982	0.238
1983	1.048
1984	1.475
1985	1.324
1986	1.393
1987	1.263
1988	1.688
1989	1.108
1990	0.967
1991	1.6
1992	1.5