# asia_russ039w - Pinega - 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/4591
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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_russ039w - Pinega - 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: Pinega
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 64.92
#	Southernmost_Latitude: 64.92
#	Easternmost_Longitude: 42.5
#	Westernmost_Longitude: 42.5
#	Elevation: 230 m
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# Data_Collection
#	Collection_Name: asia_russ039wB
#	Earliest_Year: 1736
#	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":"5.51337070705","T2":"19.2188996987","M1":"0.022823301358","M2":"0.317490669609"}}
#--------------------
# 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
1736	0.936
1737	0.834
1738	0.699
1739	1.004
1740	1.065
1741	1.18
1742	0.985
1743	0.959
1744	0.916
1745	0.968
1746	1.034
1747	1.433
1748	1.378
1749	1.225
1750	0.898
1751	0.768
1752	0.762
1753	0.936
1754	1.244
1755	1.014
1756	1.307
1757	1.464
1758	0.85
1759	1.055
1760	0.946
1761	1.193
1762	1.094
1763	1.388
1764	1.4
1765	1.505
1766	1.293
1767	1.471
1768	1.388
1769	1.426
1770	1.349
1771	1.651
1772	0.977
1773	0.83
1774	0.601
1775	0.734
1776	0.859
1777	0.92
1778	0.861
1779	0.779
1780	1.049
1781	1.408
1782	1.363
1783	1.174
1784	1.223
1785	1.13
1786	1.073
1787	0.966
1788	0.64
1789	0.393
1790	0.556
1791	0.782
1792	0.857
1793	0.801
1794	0.766
1795	0.842
1796	1.067
1797	1.122
1798	1.324
1799	0.985
1800	0.909
1801	0.987
1802	0.835
1803	0.745
1804	0.966
1805	1.139
1806	0.821
1807	0.983
1808	0.973
1809	1.116
1810	0.704
1811	0.898
1812	0.795
1813	0.573
1814	0.762
1815	0.655
1816	0.519
1817	0.38
1818	0.546
1819	0.612
1820	0.608
1821	0.462
1822	0.524
1823	0.795
1824	0.995
1825	1.024
1826	1.109
1827	0.987
1828	1.124
1829	1.448
1830	1.264
1831	1.121
1832	1.088
1833	1.395
1834	1.348
1835	1.235
1836	0.777
1837	0.899
1838	0.821
1839	0.469
1840	0.332
1841	0.394
1842	0.206
1843	0.272
1844	0.333
1845	0.312
1846	0.334
1847	0.465
1848	0.431
1849	0.581
1850	0.658
1851	0.884
1852	0.807
1853	0.977
1854	0.845
1855	1.033
1856	1.141
1857	0.842
1858	0.788
1859	0.717
1860	1.01
1861	1.256
1862	0.97
1863	0.992
1864	1.192
1865	0.994
1866	1.216
1867	1.266
1868	1.263
1869	1.099
1870	0.774
1871	0.736
1872	0.976
1873	1.056
1874	1.118
1875	1.017
1876	0.777
1877	0.841
1878	1.201
1879	0.957
1880	1.043
1881	0.978
1882	0.939
1883	1.205
1884	1.385
1885	1.575
1886	1.093
1887	0.922
1888	1.011
1889	1.301
1890	1.616
1891	1.265
1892	1.453
1893	1.343
1894	1.142
1895	1.023
1896	1.21
1897	0.755
1898	1.116
1899	0.935
1900	1.046
1901	1.225
1902	1.209
1903	0.924
1904	1.292
1905	1.248
1906	1.282
1907	1.282
1908	1.258
1909	1.069
1910	0.976
1911	1.051
1912	0.985
1913	1.171
1914	1.02
1915	1.085
1916	1.099
1917	1.194
1918	0.953
1919	0.946
1920	0.634
1921	0.91
1922	1.13
1923	1.277
1924	1.335
1925	1.627
1926	1.344
1927	1.465
1928	1.108
1929	1.146
1930	0.997
1931	1.265
1932	1.08
1933	1.157
1934	1.312
1935	1.1
1936	1.177
1937	0.997
1938	1.17
1939	1.083
1940	1.135
1941	1.148
1942	1.132
1943	1.121
1944	1.038
1945	1.153
1946	0.938
1947	0.912
1948	1.019
1949	0.959
1950	0.957
1951	1.103
1952	1.108
1953	1.18
1954	1.173
1955	0.915
1956	1.029
1957	0.993
1958	0.878
1959	1.059
1960	0.89
1961	0.845
1962	0.555
1963	0.699
1964	1.042
1965	0.95
1966	0.996
1967	0.626
1968	0.744
1969	0.709
1970	0.949
1971	0.575
1972	0.679
1973	0.618
1974	0.724
1975	0.388
1976	0.57
1977	0.838
1978	0.763
1979	0.946
1980	0.792
1981	0.821
1982	0.674
1983	0.878
1984	0.98
1985	0.794
1986	0.673
1987	0.789
1988	0.785
1989	0.515
1990	0.49