# northamerica_usa_or033 - Bally Mountain - 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:
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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/5229
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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: northamerica_usa_or033 - Bally Mountain - 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: Bally Mountain
#	Location:
#	Country: United States
#	Northernmost_Latitude: 45.28
#	Southernmost_Latitude: 45.28
#	Easternmost_Longitude: -118.57
#	Westernmost_Longitude: -118.57
#	Elevation: 0 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_or033B
#	Earliest_Year: 1699
#	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":"3.71602604878","T2":"15.5264048193","M1":"0.0228392146128","M2":"0.516040336623"}}
#--------------------
# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
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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
1699	1.176
1700	0.794
1701	0.755
1702	1.323
1703	1.17
1704	1.153
1705	0.806
1706	1.012
1707	1.14
1708	1.009
1709	0.71
1710	1.17
1711	1.193
1712	1.235
1713	1.012
1714	1.273
1715	1.522
1716	1.59
1717	0.738
1718	0.746
1719	1.043
1720	1.207
1721	1.077
1722	1.008
1723	1.176
1724	0.941
1725	0.88
1726	0.908
1727	1.367
1728	1.046
1729	1.001
1730	0.978
1731	0.902
1732	1.426
1733	1.143
1734	1.081
1735	0.904
1736	0.587
1737	0.818
1738	1.057
1739	0.812
1740	0.481
1741	0.405
1742	0.592
1743	0.73
1744	0.445
1745	0.745
1746	0.841
1747	1.045
1748	0.944
1749	0.932
1750	1.737
1751	1.282
1752	0.496
1753	0.478
1754	0.389
1755	0.937
1756	0.598
1757	0.624
1758	0.654
1759	0.63
1760	0.806
1761	1.209
1762	1.154
1763	1.222
1764	0.721
1765	0.949
1766	1.12
1767	1.136
1768	1.167
1769	1.181
1770	1.61
1771	1.399
1772	1.113
1773	1.673
1774	1.348
1775	1.062
1776	0.709
1777	0.652
1778	0.863
1779	0.851
1780	0.559
1781	0.848
1782	0.799
1783	0.65
1784	0.757
1785	0.744
1786	0.852
1787	0.587
1788	0.718
1789	0.914
1790	0.73
1791	1.28
1792	0.907
1793	1.025
1794	0.773
1795	0.695
1796	0.743
1797	0.509
1798	0.728
1799	0.824
1800	0.572
1801	0.907
1802	1.174
1803	1.026
1804	0.732
1805	1.037
1806	0.92
1807	0.796
1808	0.787
1809	0.812
1810	0.847
1811	1.125
1812	1.213
1813	0.965
1814	0.875
1815	0.938
1816	1.217
1817	0.879
1818	1.086
1819	1.24
1820	0.718
1821	0.866
1822	1.334
1823	0.838
1824	1.106
1825	1.483
1826	1.281
1827	0.721
1828	0.987
1829	0.972
1830	0.79
1831	0.381
1832	0.816
1833	0.804
1834	0.92
1835	0.418
1836	0.706
1837	0.726
1838	1.104
1839	1.1
1840	0.609
1841	0.653
1842	0.739
1843	0.856
1844	0.841
1845	0.974
1846	0.581
1847	0.275
1848	0.529
1849	0.403
1850	0.366
1851	0.666
1852	0.696
1853	0.877
1854	0.865
1855	1.312
1856	1.133
1857	1.343
1858	1.135
1859	0.872
1860	0.817
1861	1.013
1862	1.159
1863	1.104
1864	0.988
1865	0.81
1866	0.945
1867	0.848
1868	1.081
1869	0.821
1870	0.84
1871	0.65
1872	0.549
1873	0.715
1874	0.696
1875	0.811
1876	0.868
1877	1.347
1878	1.326
1879	1.241
1880	0.97
1881	1.054
1882	0.821
1883	0.561
1884	1.0
1885	1.269
1886	0.547
1887	0.555
1888	0.651
1889	0.565
1890	0.337
1891	1.098
1892	1.029
1893	0.978
1894	1.462
1895	1.219
1896	1.157
1897	1.366
1898	1.521
1899	0.849
1900	2.015
1901	1.766
1902	1.241
1903	1.75
1904	2.235
1905	1.421
1906	1.492
1907	1.953
1908	1.919
1909	1.325
1910	1.22
1911	1.146
1912	1.173
1913	1.581
1914	1.582
1915	1.53
1916	1.346
1917	1.018
1918	0.953
1919	1.186
1920	0.683
1921	1.18
1922	0.951
1923	0.997
1924	0.99
1925	0.662
1926	0.682
1927	1.031
1928	0.894
1929	0.642
1930	0.36
1931	0.61
1932	0.568
1933	0.506
1934	0.973
1935	0.449
1936	0.384
1937	0.674
1938	0.996
1939	0.963
1940	0.947
1941	1.526
1942	2.128
1943	1.353
1944	1.074
1945	0.93
1946	1.346
1947	1.605
1948	1.297
1949	1.051
1950	1.007
1951	0.964
1952	0.989
1953	0.926
1954	1.043
1955	1.089
1956	1.007
1957	0.985
1958	1.145
1959	0.812
1960	1.023
1961	0.873
1962	0.726
1963	0.709
1964	0.699
1965	0.765
1966	0.871
1967	0.624
1968	0.507
1969	1.106
1970	0.611
1971	0.859
1972	0.682
1973	0.339
1974	0.544
1975	0.624
1976	0.816
1977	0.833
1978	0.85
1979	0.799
1980	0.945
1981	1.152
1982	1.261
1983	1.446
1984	1.074
1985	0.976
1986	1.072
1987	1.005
1988	0.717
1989	0.674
1990	1.358