# northamerica_usa_sd016 - Pilger 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.
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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/3959
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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_sd016 - Pilger 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: Pilger Mountain
#	Location:
#	Country: United States
#	Northernmost_Latitude: 43.5
#	Southernmost_Latitude: 43.5
#	Easternmost_Longitude: -103.88
#	Westernmost_Longitude: -103.88
#	Elevation: 1392 m
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# Data_Collection
#	Collection_Name: northamerica_usa_sd016B
#	Earliest_Year: 1717
#	Most_Recent_Year: 1989
#	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":"4.24623129245","T2":"14.9204103462","M1":"0.0225196120493","M2":"0.521066050512"}}
#--------------------
# 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
#
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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
1717	1.076
1718	1.034
1719	1.495
1720	0.748
1721	0.306
1722	1.006
1723	0.809
1724	0.737
1725	0.938
1726	1.657
1727	1.552
1728	1.032
1729	1.298
1730	1.109
1731	0.912
1732	0.885
1733	0.872
1734	0.636
1735	0.656
1736	0.34
1737	1.086
1738	0.876
1739	0.726
1740	1.232
1741	0.5
1742	0.751
1743	0.455
1744	0.762
1745	1.05
1746	0.866
1747	0.812
1748	1.351
1749	1.007
1750	1.167
1751	1.036
1752	1.023
1753	0.601
1754	0.872
1755	0.937
1756	0.555
1757	0.336
1758	0.137
1759	0.155
1760	0.358
1761	1.168
1762	0.92
1763	1.285
1764	1.574
1765	1.814
1766	1.602
1767	1.874
1768	1.696
1769	1.611
1770	2.189
1771	1.676
1772	1.25
1773	1.488
1774	1.436
1775	1.66
1776	1.136
1777	1.687
1778	1.606
1779	1.321
1780	1.931
1781	1.161
1782	0.937
1783	1.213
1784	0.823
1785	0.423
1786	0.931
1787	0.749
1788	0.842
1789	0.839
1790	0.765
1791	0.834
1792	1.25
1793	1.381
1794	1.218
1795	1.142
1796	1.197
1797	0.973
1798	0.63
1799	0.778
1800	0.825
1801	0.886
1802	1.09
1803	0.974
1804	1.203
1805	1.049
1806	1.14
1807	0.504
1808	0.464
1809	0.508
1810	0.615
1811	0.626
1812	0.756
1813	0.935
1814	1.081
1815	0.606
1816	1.084
1817	0.484
1818	0.69
1819	0.695
1820	1.041
1821	0.953
1822	0.565
1823	0.438
1824	0.686
1825	0.774
1826	0.767
1827	0.831
1828	0.945
1829	1.272
1830	1.541
1831	1.081
1832	1.27
1833	0.898
1834	1.199
1835	1.246
1836	1.598
1837	1.441
1838	1.366
1839	1.214
1840	1.403
1841	1.56
1842	1.641
1843	1.301
1844	1.329
1845	0.811
1846	0.926
1847	0.331
1848	0.095
1849	0.972
1850	0.855
1851	1.058
1852	0.695
1853	0.928
1854	0.939
1855	0.565
1856	0.361
1857	0.777
1858	0.568
1859	0.28
1860	0.286
1861	0.379
1862	0.542
1863	0.131
1864	0.298
1865	0.043
1866	0.347
1867	0.421
1868	0.555
1869	0.798
1870	0.284
1871	0.448
1872	0.566
1873	0.897
1874	0.483
1875	0.984
1876	0.045
1877	-0.049
1878	0.419
1879	0.909
1880	0.706
1881	0.701
1882	1.196
1883	1.252
1884	0.947
1885	1.319
1886	1.311
1887	1.129
1888	1.342
1889	1.174
1890	1.31
1891	1.097
1892	1.095
1893	0.433
1894	1.0
1895	0.805
1896	0.727
1897	0.596
1898	0.725
1899	0.818
1900	0.82
1901	0.969
1902	1.318
1903	1.306
1904	1.463
1905	1.82
1906	1.868
1907	1.364
1908	1.594
1909	1.427
1910	0.944
1911	0.241
1912	1.004
1913	0.935
1914	0.794
1915	1.82
1916	1.442
1917	0.765
1918	1.816
1919	0.756
1920	0.531
1921	1.078
1922	1.525
1923	1.073
1924	0.852
1925	1.157
1926	1.204
1927	1.017
1928	0.99
1929	0.966
1930	0.913
1931	0.771
1932	1.285
1933	0.94
1934	0.115
1935	0.733
1936	0.885
1937	1.147
1938	1.302
1939	0.051
1940	0.634
1941	1.525
1942	1.582
1943	1.218
1944	1.357
1945	2.312
1946	2.203
1947	1.859
1948	1.899
1949	1.111
1950	0.991
1951	1.112
1952	1.257
1953	1.406
1954	0.801
1955	1.453
1956	1.229
1957	1.095
1958	1.295
1959	0.794
1960	0.606
1961	0.331
1962	1.171
1963	1.168
1964	0.411
1965	1.287
1966	1.23
1967	1.011
1968	0.989
1969	1.106
1970	0.532
1971	0.953
1972	0.966
1973	0.532
1974	0.218
1975	1.077
1976	1.007
1977	0.173
1978	0.659
1979	0.403
1980	0.449
1981	0.502
1982	0.704
1983	0.68
1984	0.697
1985	0.402
1986	0.968
1987	0.851
1988	0.18
1989	0.208