# northamerica_usa_wa038 - Colockum Pass - 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/2884
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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_wa038 - Colockum Pass - 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: Colockum Pass
#	Location:
#	Country: United States
#	Northernmost_Latitude: 47.2
#	Southernmost_Latitude: 47.2
#	Easternmost_Longitude: -120.28
#	Westernmost_Longitude: -120.28
#	Elevation: 1670 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa038B
#	Earliest_Year: 1713
#	Most_Recent_Year: 1975
#	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":"5.24441861342","T2":"16.7485412504","M1":"0.0220977915273","M2":"0.405985222621"}}
#--------------------
# 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
1713	0.772
1714	0.672
1715	0.977
1716	1.129
1717	0.755
1718	0.77
1719	0.838
1720	0.909
1721	0.701
1722	0.819
1723	1.039
1724	0.797
1725	0.804
1726	0.826
1727	1.498
1728	1.415
1729	1.14
1730	0.933
1731	1.102
1732	1.195
1733	1.393
1734	1.06
1735	1.104
1736	1.104
1737	1.17
1738	1.257
1739	1.37
1740	0.863
1741	0.874
1742	1.16
1743	0.972
1744	0.977
1745	1.355
1746	1.337
1747	1.354
1748	1.124
1749	1.232
1750	1.547
1751	1.146
1752	1.048
1753	1.119
1754	1.052
1755	1.149
1756	0.879
1757	0.943
1758	0.949
1759	0.808
1760	0.868
1761	1.364
1762	1.193
1763	1.251
1764	1.118
1765	1.372
1766	1.185
1767	1.122
1768	1.106
1769	1.1
1770	1.132
1771	1.153
1772	0.965
1773	1.169
1774	1.1
1775	1.062
1776	0.747
1777	0.548
1778	0.661
1779	0.953
1780	0.971
1781	0.909
1782	0.789
1783	0.764
1784	0.534
1785	0.677
1786	0.692
1787	0.516
1788	0.72
1789	0.8
1790	0.819
1791	1.144
1792	0.831
1793	0.965
1794	0.854
1795	0.863
1796	0.845
1797	0.469
1798	0.442
1799	0.566
1800	0.768
1801	0.642
1802	0.686
1803	0.813
1804	0.997
1805	1.246
1806	1.013
1807	1.042
1808	1.048
1809	1.08
1810	1.094
1811	1.087
1812	1.13
1813	0.736
1814	0.955
1815	0.908
1816	0.874
1817	0.823
1818	0.918
1819	1.106
1820	0.907
1821	0.943
1822	1.149
1823	0.719
1824	1.008
1825	1.127
1826	0.88
1827	0.908
1828	1.033
1829	1.148
1830	0.781
1831	0.877
1832	0.945
1833	1.244
1834	1.146
1835	0.873
1836	0.99
1837	1.091
1838	1.133
1839	1.083
1840	0.739
1841	0.664
1842	0.567
1843	0.756
1844	0.823
1845	1.024
1846	0.879
1847	0.819
1848	0.822
1849	0.602
1850	0.739
1851	0.916
1852	0.895
1853	0.848
1854	1.062
1855	1.455
1856	1.101
1857	1.349
1858	1.086
1859	0.84
1860	0.812
1861	1.075
1862	1.059
1863	1.11
1864	1.048
1865	0.868
1866	0.992
1867	0.896
1868	1.084
1869	0.954
1870	0.868
1871	0.776
1872	0.783
1873	0.872
1874	0.828
1875	0.48
1876	0.662
1877	1.112
1878	1.164
1879	0.891
1880	0.953
1881	1.258
1882	1.212
1883	0.869
1884	0.94
1885	1.061
1886	0.854
1887	0.857
1888	1.068
1889	0.779
1890	0.678
1891	0.681
1892	0.623
1893	0.701
1894	0.894
1895	0.941
1896	0.741
1897	0.983
1898	0.942
1899	0.825
1900	1.16
1901	1.539
1902	1.271
1903	1.133
1904	1.523
1905	1.495
1906	1.506
1907	1.447
1908	1.791
1909	1.147
1910	1.152
1911	1.173
1912	0.903
1913	1.4
1914	1.61
1915	1.25
1916	1.129
1917	1.193
1918	1.291
1919	1.269
1920	0.724
1921	1.262
1922	1.026
1923	0.971
1924	1.11
1925	0.99
1926	0.974
1927	0.972
1928	1.294
1929	0.946
1930	1.129
1931	1.083
1932	0.967
1933	0.96
1934	1.276
1935	0.9
1936	0.876
1937	1.142
1938	1.216
1939	0.903
1940	0.987
1941	1.109
1942	1.192
1943	0.845
1944	1.029
1945	0.943
1946	0.697
1947	0.922
1948	0.928
1949	0.948
1950	0.826
1951	0.997
1952	0.965
1953	0.84
1954	0.933
1955	1.069
1956	1.193
1957	0.986
1958	0.932
1959	0.928
1960	0.973
1961	0.836
1962	0.949
1963	0.868
1964	0.892
1965	0.891
1966	1.023
1967	0.817
1968	0.733
1969	0.867
1970	0.671
1971	0.56
1972	0.764
1973	0.759
1974	0.668
1975	0.435