# asia_russ031w - Ozera Lama - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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/4579
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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_russ031w - Ozera Lama - 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: Ozera Lama
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 69.58
#	Southernmost_Latitude: 69.58
#	Easternmost_Longitude: 90.5
#	Westernmost_Longitude: 90.5
#	Elevation: 60 m
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# Data_Collection
#	Collection_Name: asia_russ031wB
#	Earliest_Year: 1730
#	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":"2.69115449912","T2":"17.0333820997","M1":"0.0227247931849","M2":"0.458611565136"}}
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# Species
#	Species_Name: Siberian spruce
#	Species_Code: PCOB
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# Chronology:
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# Variables
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# 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
1730	1.59
1731	0.848
1732	0.909
1733	1.38
1734	1.132
1735	0.939
1736	0.789
1737	0.964
1738	0.559
1739	0.882
1740	1.03
1741	0.863
1742	0.536
1743	1.246
1744	1.236
1745	0.94
1746	1.182
1747	1.65
1748	1.601
1749	1.532
1750	1.292
1751	0.897
1752	0.562
1753	1.108
1754	0.859
1755	0.879
1756	0.888
1757	0.75
1758	0.579
1759	0.285
1760	0.746
1761	0.995
1762	1.419
1763	0.753
1764	1.0
1765	1.058
1766	1.203
1767	1.6
1768	0.961
1769	0.871
1770	0.645
1771	0.868
1772	0.741
1773	0.757
1774	0.917
1775	1.462
1776	0.558
1777	0.747
1778	0.615
1779	0.513
1780	0.529
1781	0.479
1782	0.806
1783	0.548
1784	0.917
1785	1.161
1786	1.246
1787	1.295
1788	1.139
1789	1.493
1790	1.165
1791	1.176
1792	0.855
1793	1.637
1794	1.543
1795	1.35
1796	1.499
1797	0.758
1798	0.858
1799	0.964
1800	0.89
1801	1.334
1802	0.914
1803	0.982
1804	0.849
1805	1.329
1806	1.271
1807	0.633
1808	1.121
1809	1.082
1810	1.141
1811	0.747
1812	0.464
1813	0.742
1814	0.75
1815	0.611
1816	0.494
1817	0.366
1818	0.38
1819	0.163
1820	0.391
1821	0.644
1822	0.574
1823	0.383
1824	0.331
1825	0.369
1826	0.751
1827	0.895
1828	0.633
1829	1.127
1830	0.555
1831	1.127
1832	0.882
1833	0.384
1834	1.13
1835	1.371
1836	1.004
1837	0.731
1838	1.115
1839	1.181
1840	1.084
1841	0.869
1842	1.517
1843	0.999
1844	1.478
1845	1.113
1846	1.235
1847	0.833
1848	1.038
1849	0.972
1850	1.062
1851	0.993
1852	1.023
1853	1.199
1854	0.773
1855	0.598
1856	0.919
1857	0.863
1858	1.078
1859	0.739
1860	0.935
1861	1.112
1862	0.877
1863	0.995
1864	0.808
1865	0.832
1866	0.606
1867	0.319
1868	0.995
1869	0.682
1870	1.085
1871	0.692
1872	0.743
1873	0.588
1874	0.564
1875	0.744
1876	0.807
1877	1.112
1878	1.138
1879	1.229
1880	1.24
1881	0.86
1882	0.901
1883	0.818
1884	0.845
1885	0.582
1886	0.993
1887	0.797
1888	0.724
1889	0.672
1890	0.767
1891	0.963
1892	1.237
1893	1.314
1894	1.136
1895	0.688
1896	0.96
1897	1.627
1898	1.325
1899	1.139
1900	0.96
1901	0.764
1902	0.703
1903	1.208
1904	1.272
1905	0.901
1906	0.993
1907	1.043
1908	1.975
1909	1.495
1910	1.335
1911	0.84
1912	1.052
1913	0.851
1914	0.648
1915	1.304
1916	0.871
1917	0.936
1918	1.272
1919	0.85
1920	1.014
1921	0.777
1922	0.897
1923	0.797
1924	0.985
1925	0.626
1926	1.173
1927	0.735
1928	1.387
1929	0.954
1930	1.307
1931	0.935
1932	1.025
1933	0.773
1934	1.239
1935	1.068
1936	1.39
1937	1.134
1938	1.006
1939	0.95
1940	0.996
1941	1.043
1942	1.612
1943	1.188
1944	1.322
1945	1.7
1946	1.548
1947	1.316
1948	1.585
1949	1.305
1950	1.641
1951	1.279
1952	1.487
1953	1.749
1954	1.186
1955	1.374
1956	1.282
1957	1.233
1958	0.883
1959	1.321
1960	0.479
1961	0.698
1962	0.9
1963	0.518
1964	0.753
1965	0.861
1966	0.78
1967	1.007
1968	0.743
1969	1.189
1970	0.716
1971	0.645
1972	0.691
1973	0.468
1974	0.168
1975	0.59
1976	0.826
1977	0.705
1978	0.834
1979	0.94
1980	0.63
1981	0.93
1982	0.601
1983	0.744
1984	1.275
1985	0.806
1986	0.965
1987	0.538
1988	0.97
1989	0.6
1990	1.514