# northamerica_usa_wa125 - Blue Mountain Low - 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/4113
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
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# Contribution_Date
#	Date: 2016-01-07
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# Title
#	Study_Name: northamerica_usa_wa125 - Blue Mountain Low - Breitenmoser Tree Ring Chronology Data
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# 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: Blue Mountain Low
#	Location:
#	Country: United States
#	Northernmost_Latitude: 47.92
#	Southernmost_Latitude: 47.92
#	Easternmost_Longitude: -123.25
#	Westernmost_Longitude: -123.25
#	Elevation: 1340 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa125B
#	Earliest_Year: 1850
#	Most_Recent_Year: 1991
#	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":"5.6599949637","T2":"17.017018485","M1":"0.0227957905728","M2":"0.445750386854"}}
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# Species
#	Species_Name: subalpine fir
#	Species_Code: ABLA
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# Chronology:
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# Variables
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# 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
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age	trsgi
1850	1.027
1851	0.848
1852	0.78
1853	0.924
1854	0.821
1855	0.818
1856	0.908
1857	0.851
1858	0.836
1859	0.885
1860	0.986
1861	0.975
1862	1.127
1863	1.134
1864	0.782
1865	0.988
1866	1.077
1867	1.093
1868	1.09
1869	0.817
1870	0.94
1871	0.634
1872	0.787
1873	0.936
1874	0.876
1875	0.866
1876	0.676
1877	0.705
1878	0.932
1879	0.99
1880	0.94
1881	0.918
1882	1.19
1883	0.788
1884	0.963
1885	0.877
1886	0.941
1887	0.882
1888	0.861
1889	0.713
1890	0.977
1891	0.878
1892	0.896
1893	0.859
1894	1.048
1895	0.912
1896	0.683
1897	0.8
1898	0.748
1899	0.73
1900	0.811
1901	0.942
1902	0.971
1903	1.071
1904	0.991
1905	0.942
1906	0.827
1907	1.0
1908	0.994
1909	0.953
1910	0.958
1911	1.077
1912	1.123
1913	1.109
1914	1.064
1915	1.155
1916	1.115
1917	0.954
1918	1.026
1919	1.17
1920	1.264
1921	1.199
1922	1.028
1923	1.315
1924	0.915
1925	1.112
1926	0.853
1927	1.183
1928	1.067
1929	1.027
1930	0.916
1931	0.962
1932	0.971
1933	1.09
1934	0.929
1935	1.187
1936	1.095
1937	1.092
1938	0.942
1939	1.37
1940	1.107
1941	1.233
1942	1.345
1943	1.008
1944	1.151
1945	0.981
1946	1.211
1947	1.114
1948	1.425
1949	1.244
1950	1.309
1951	1.038
1952	1.342
1953	1.04
1954	1.338
1955	1.58
1956	1.183
1957	1.185
1958	1.34
1959	1.009
1960	1.037
1961	1.08
1962	0.922
1963	1.161
1964	1.186
1965	1.108
1966	1.164
1967	1.192
1968	0.846
1969	1.025
1970	0.834
1971	0.934
1972	0.93
1973	0.855
1974	0.812
1975	0.717
1976	0.858
1977	0.823
1978	0.745
1979	0.765
1980	0.835
1981	0.869
1982	0.734
1983	0.59
1984	0.825
1985	0.849
1986	0.692
1987	0.617
1988	0.501
1989	0.638
1990	0.727
1991	0.653