# asia_russ040w - Nonburg - 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:
#
# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611
#
# Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/4562
#
# Description/Documentation lines begin with #
# Data lines have no #
#
# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: asia_russ040w - Nonburg - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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.
#------------------
# 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
#------------------
# Site_Information
#	Site_Name: Nonburg
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 65.6
#	Southernmost_Latitude: 65.6
#	Easternmost_Longitude: 50.63
#	Westernmost_Longitude: 50.63
#	Elevation: 70 m
#--------------------
# Data_Collection
#	Collection_Name: asia_russ040wB
#	Earliest_Year: 1709
#	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":"7.50726851229","T2":"18.9949207275","M1":"0.0224841984989","M2":"0.226712869953"}}
#--------------------
# Species
#	Species_Name: Siberian spruce
#	Species_Code: PCOB
#--------------------
# Chronology:
#
#
#
#--------------------
# 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
1709	1.138
1710	1.251
1711	0.858
1712	0.691
1713	0.583
1714	0.724
1715	0.537
1716	0.781
1717	0.769
1718	0.627
1719	0.974
1720	0.945
1721	0.995
1722	0.713
1723	0.981
1724	0.944
1725	1.051
1726	1.028
1727	1.183
1728	1.219
1729	0.991
1730	1.106
1731	1.097
1732	0.69
1733	0.723
1734	0.485
1735	0.662
1736	0.448
1737	0.725
1738	0.563
1739	0.697
1740	0.455
1741	0.576
1742	0.65
1743	0.656
1744	0.849
1745	0.994
1746	0.764
1747	0.635
1748	0.383
1749	0.868
1750	0.631
1751	0.683
1752	0.605
1753	1.062
1754	1.112
1755	0.904
1756	1.416
1757	1.126
1758	1.132
1759	1.014
1760	1.006
1761	1.28
1762	1.214
1763	0.852
1764	0.996
1765	0.878
1766	0.314
1767	0.86
1768	0.911
1769	1.038
1770	0.69
1771	0.933
1772	-0.051
1773	0.237
1774	0.208
1775	0.155
1776	0.368
1777	0.417
1778	0.194
1779	0.24
1780	0.29
1781	0.388
1782	0.509
1783	0.518
1784	0.489
1785	0.449
1786	0.358
1787	0.267
1788	0.481
1789	0.23
1790	0.567
1791	0.621
1792	0.446
1793	0.495
1794	0.323
1795	0.485
1796	0.632
1797	0.363
1798	0.653
1799	0.679
1800	0.864
1801	1.093
1802	0.88
1803	0.817
1804	0.765
1805	1.146
1806	0.955
1807	1.012
1808	0.75
1809	0.84
1810	0.457
1811	0.514
1812	0.589
1813	0.671
1814	0.381
1815	0.387
1816	0.414
1817	0.235
1818	0.347
1819	0.467
1820	0.491
1821	0.56
1822	0.642
1823	1.091
1824	0.987
1825	1.236
1826	1.194
1827	1.944
1828	2.014
1829	2.701
1830	2.377
1831	2.176
1832	2.086
1833	2.127
1834	1.828
1835	1.569
1836	1.195
1837	1.319
1838	1.099
1839	1.585
1840	0.962
1841	1.057
1842	1.312
1843	1.316
1844	1.694
1845	1.391
1846	1.547
1847	1.462
1848	1.197
1849	1.176
1850	1.126
1851	1.359
1852	1.085
1853	0.977
1854	1.062
1855	1.164
1856	1.64
1857	1.09
1858	0.844
1859	1.26
1860	0.823
1861	0.888
1862	0.836
1863	0.632
1864	1.065
1865	0.71
1866	0.896
1867	0.863
1868	0.783
1869	0.954
1870	0.728
1871	0.627
1872	1.043
1873	1.038
1874	0.717
1875	0.808
1876	0.837
1877	1.195
1878	1.629
1879	1.024
1880	1.349
1881	1.118
1882	1.024
1883	1.557
1884	1.431
1885	1.746
1886	1.447
1887	1.631
1888	1.09
1889	1.287
1890	1.659
1891	1.124
1892	2.0
1893	1.529
1894	1.3
1895	1.143
1896	1.267
1897	0.95
1898	1.097
1899	1.104
1900	1.251
1901	1.388
1902	1.133
1903	0.63
1904	1.032
1905	0.816
1906	1.134
1907	1.491
1908	1.194
1909	1.197
1910	0.708
1911	1.243
1912	1.242
1913	1.805
1914	1.398
1915	1.69
1916	1.386
1917	1.593
1918	1.511
1919	1.334
1920	0.858
1921	1.042
1922	1.258
1923	1.29
1924	0.91
1925	1.376
1926	1.282
1927	1.507
1928	1.239
1929	1.268
1930	0.882
1931	1.014
1932	0.665
1933	0.791
1934	0.812
1935	0.736
1936	1.107
1937	0.931
1938	1.254
1939	1.182
1940	1.23
1941	0.602
1942	0.839
1943	0.551
1944	0.564
1945	0.764
1946	0.673
1947	0.676
1948	0.878
1949	0.774
1950	0.496
1951	0.807
1952	1.235
1953	1.328
1954	1.245
1955	0.88
1956	1.259
1957	1.062
1958	0.809
1959	1.162
1960	0.79
1961	0.716
1962	0.201
1963	0.45
1964	0.879
1965	0.874
1966	0.733
1967	0.367
1968	0.748
1969	0.766
1970	0.833
1971	0.681
1972	0.582
1973	0.477
1974	0.681
1975	0.007
1976	0.554
1977	0.43
1978	0.392
1979	0.631
1980	0.484
1981	0.647
1982	0.077
1983	0.676
1984	0.779
1985	0.502
1986	0.46
1987	0.658
1988	0.775
1989	0.524
1990	0.562