# asia_russ098w - Pinega, Belomop-kuloi pla - 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/4593
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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_russ098w - Pinega, Belomop-kuloi pla - 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: Pinega, Belomop-kuloi pla
#	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_russ098wB
#	Earliest_Year: 1695
#	Most_Recent_Year: 1990
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"6.40562577232","T2":"16.3682510759","M1":"0.0228590631053","M2":"0.521716946438"}}
#--------------------
# 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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1695	0.938
1696	1.095
1697	1.257
1698	1.019
1699	0.811
1700	0.662
1701	0.803
1702	0.701
1703	0.798
1704	0.868
1705	1.098
1706	0.64
1707	1.377
1708	1.189
1709	1.08
1710	1.055
1711	0.967
1712	0.31
1713	1.052
1714	1.123
1715	1.205
1716	1.413
1717	0.566
1718	1.081
1719	0.415
1720	0.36
1721	0.692
1722	0.816
1723	0.909
1724	1.15
1725	1.2
1726	1.307
1727	1.519
1728	1.331
1729	1.268
1730	0.938
1731	1.548
1732	1.195
1733	1.369
1734	1.23
1735	1.229
1736	1.787
1737	1.71
1738	1.638
1739	1.75
1740	1.367
1741	1.014
1742	1.022
1743	0.85
1744	0.933
1745	1.348
1746	1.283
1747	1.397
1748	0.926
1749	1.051
1750	0.484
1751	0.862
1752	1.334
1753	1.001
1754	1.328
1755	1.605
1756	1.09
1757	0.869
1758	1.41
1759	0.917
1760	0.964
1761	0.776
1762	1.248
1763	1.265
1764	0.943
1765	0.973
1766	0.704
1767	1.443
1768	1.216
1769	0.9
1770	0.613
1771	0.82
1772	0.268
1773	0.637
1774	1.425
1775	1.491
1776	0.296
1777	0.102
1778	0.211
1779	0.665
1780	0.54
1781	0.544
1782	0.906
1783	0.809
1784	0.616
1785	0.717
1786	0.324
1787	0.529
1788	0.714
1789	0.719
1790	0.988
1791	0.584
1792	0.479
1793	0.562
1794	0.94
1795	1.238
1796	1.372
1797	1.537
1798	1.207
1799	1.5
1800	1.373
1801	1.052
1802	1.247
1803	1.037
1804	0.578
1805	0.013
1806	0.25
1807	0.475
1808	0.43
1809	0.688
1810	0.133
1811	0.526
1812	0.495
1813	0.135
1814	0.245
1815	0.056
1816	0.317
1817	0.345
1818	0.477
1819	0.948
1820	0.972
1821	0.567
1822	0.562
1823	1.79
1824	1.643
1825	2.225
1826	2.791
1827	2.604
1828	2.661
1829	1.777
1830	1.766
1831	1.231
1832	1.017
1833	1.305
1834	0.643
1835	0.75
1836	-0.024
1837	0.557
1838	0.301
1839	0.404
1840	0.89
1841	1.058
1842	1.492
1843	1.424
1844	1.328
1845	0.66
1846	0.289
1847	1.063
1848	1.132
1849	1.295
1850	1.516
1851	1.463
1852	1.347
1853	1.353
1854	0.276
1855	0.387
1856	0.894
1857	0.692
1858	0.543
1859	0.913
1860	1.235
1861	1.456
1862	0.749
1863	0.687
1864	1.462
1865	1.246
1866	1.017
1867	0.625
1868	0.215
1869	0.773
1870	0.874
1871	0.488
1872	0.354
1873	0.306
1874	0.211
1875	0.696
1876	0.969
1877	1.346
1878	1.557
1879	0.863
1880	1.253
1881	1.198
1882	0.629
1883	1.225
1884	1.386
1885	1.344
1886	1.16
1887	1.444
1888	1.261
1889	1.125
1890	1.657
1891	1.305
1892	0.759
1893	0.594
1894	0.487
1895	0.792
1896	0.987
1897	1.319
1898	2.026
1899	1.533
1900	1.604
1901	1.736
1902	1.552
1903	0.979
1904	0.916
1905	0.179
1906	0.446
1907	0.608
1908	0.355
1909	0.385
1910	0.192
1911	0.596
1912	0.539
1913	0.318
1914	0.666
1915	0.568
1916	0.907
1917	0.85
1918	0.888
1919	0.856
1920	0.875
1921	1.625
1922	1.345
1923	1.375
1924	0.437
1925	0.74
1926	0.735
1927	0.806
1928	0.607
1929	0.637
1930	0.388
1931	0.545
1932	0.538
1933	0.954
1934	0.885
1935	0.699
1936	0.732
1937	0.852
1938	0.99
1939	1.388
1940	1.232
1941	1.052
1942	0.968
1943	1.229
1944	1.075
1945	1.105
1946	1.086
1947	1.055
1948	1.358
1949	1.742
1950	1.366
1951	1.238
1952	1.463
1953	1.4
1954	1.525
1955	1.108
1956	1.431
1957	1.333
1958	1.264
1959	1.261
1960	1.238
1961	1.129
1962	0.716
1963	0.844
1964	1.21
1965	0.956
1966	0.895
1967	0.425
1968	0.767
1969	0.275
1970	0.679
1971	0.528
1972	0.53
1973	0.701
1974	1.109
1975	0.758
1976	1.033
1977	1.165
1978	0.95
1979	0.851
1980	0.85
1981	1.112
1982	0.513
1983	0.705
1984	1.369
1985	0.975
1986	0.813
1987	1.014
1988	1.057
1989	0.865
1990	0.911