# northamerica_usa_wa022 - Rainy Pass 1 - Breitenmoser Tree Ring Chronology Data
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#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
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# 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/2907
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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_wa022 - Rainy Pass 1 - 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.
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#	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: Rainy Pass 1
#	Location:
#	Country: United States
#	Northernmost_Latitude: 48.48
#	Southernmost_Latitude: 48.48
#	Easternmost_Longitude: -120.73
#	Westernmost_Longitude: -120.73
#	Elevation: 1468 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa022B
#	Earliest_Year: 1757
#	Most_Recent_Year: 1976
#	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":"4.76809899679","T2":"15.7135400644","M1":"0.0223506273145","M2":"0.463137788542"}}
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# Species
#	Species_Name: Engelmann spruce
#	Species_Code: PCEN
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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)
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##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
1757	0.825
1758	0.747
1759	0.621
1760	0.618
1761	0.792
1762	0.736
1763	0.722
1764	0.651
1765	0.629
1766	0.598
1767	0.692
1768	0.707
1769	0.592
1770	0.571
1771	0.799
1772	0.749
1773	0.917
1774	0.822
1775	0.658
1776	0.691
1777	0.881
1778	1.019
1779	0.997
1780	0.848
1781	0.945
1782	1.043
1783	1.015
1784	1.02
1785	0.859
1786	0.871
1787	0.752
1788	0.766
1789	0.874
1790	1.159
1791	1.337
1792	1.014
1793	0.956
1794	1.159
1795	1.122
1796	1.216
1797	0.985
1798	1.146
1799	0.898
1800	1.062
1801	0.942
1802	1.079
1803	0.863
1804	0.975
1805	1.123
1806	0.887
1807	0.903
1808	1.018
1809	1.011
1810	1.007
1811	1.06
1812	1.054
1813	0.841
1814	1.043
1815	1.062
1816	1.046
1817	1.115
1818	0.815
1819	1.098
1820	1.078
1821	1.165
1822	1.214
1823	0.984
1824	0.941
1825	1.104
1826	1.039
1827	1.084
1828	1.07
1829	1.197
1830	1.21
1831	1.271
1832	0.965
1833	1.307
1834	1.31
1835	1.031
1836	0.91
1837	1.044
1838	0.948
1839	1.178
1840	0.848
1841	1.015
1842	1.01
1843	0.906
1844	0.804
1845	1.006
1846	1.125
1847	1.089
1848	1.1
1849	0.929
1850	0.944
1851	1.053
1852	1.012
1853	0.905
1854	0.82
1855	1.142
1856	1.019
1857	1.189
1858	1.099
1859	1.257
1860	0.999
1861	1.141
1862	1.119
1863	1.363
1864	1.069
1865	1.216
1866	1.117
1867	1.001
1868	1.109
1869	0.858
1870	0.817
1871	0.795
1872	0.996
1873	1.035
1874	1.014
1875	1.099
1876	0.899
1877	1.045
1878	1.054
1879	0.824
1880	0.98
1881	1.072
1882	1.204
1883	1.211
1884	1.046
1885	1.285
1886	1.052
1887	0.835
1888	0.906
1889	0.761
1890	0.887
1891	0.963
1892	0.864
1893	0.903
1894	0.955
1895	0.929
1896	0.967
1897	1.026
1898	1.243
1899	0.902
1900	1.076
1901	1.052
1902	1.027
1903	1.194
1904	1.414
1905	1.126
1906	1.089
1907	0.948
1908	1.035
1909	0.9
1910	1.08
1911	1.212
1912	1.237
1913	1.422
1914	1.343
1915	0.991
1916	0.825
1917	1.057
1918	0.966
1919	1.029
1920	0.979
1921	0.994
1922	1.015
1923	0.854
1924	0.908
1925	0.962
1926	0.769
1927	0.768
1928	0.908
1929	0.809
1930	0.898
1931	0.766
1932	0.782
1933	0.994
1934	1.102
1935	1.004
1936	1.007
1937	0.908
1938	1.148
1939	0.842
1940	0.946
1941	0.782
1942	0.903
1943	0.72
1944	0.865
1945	0.569
1946	0.494
1947	0.686
1948	0.826
1949	1.044
1950	1.081
1951	1.023
1952	0.928
1953	0.912
1954	1.038
1955	1.164
1956	1.138
1957	1.18
1958	1.226
1959	0.904
1960	1.274
1961	1.097
1962	0.791
1963	1.007
1964	1.04
1965	1.395
1966	1.385
1967	1.208
1968	0.876
1969	1.057
1970	0.908
1971	0.772
1972	0.817
1973	0.925
1974	0.797
1975	0.912
1976	-0.006