# northamerica_usa_wa112 - Mount Rainier High - 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/4167
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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_wa112 - Mount Rainier High - 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
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# 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: Mount Rainier High
#	Location:
#	Country: United States
#	Northernmost_Latitude: 46.83
#	Southernmost_Latitude: 46.83
#	Easternmost_Longitude: -121.75
#	Westernmost_Longitude: -121.75
#	Elevation: 1830 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa112B
#	Earliest_Year: 1850
#	Most_Recent_Year: 1992
#	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":"5.23048496576","T2":"19.4846405385","M1":"0.0223519310122","M2":"0.331209570389"}}
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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
#
age	trsgi
1850	0.726
1851	0.932
1852	0.942
1853	0.666
1854	0.626
1855	1.185
1856	0.823
1857	0.831
1858	0.736
1859	0.833
1860	0.899
1861	0.887
1862	0.889
1863	1.246
1864	0.891
1865	1.189
1866	0.768
1867	0.677
1868	0.785
1869	0.926
1870	0.944
1871	1.005
1872	1.055
1873	0.973
1874	1.181
1875	0.98
1876	0.584
1877	1.049
1878	0.684
1879	1.027
1880	0.66
1881	0.611
1882	0.81
1883	0.786
1884	0.763
1885	0.973
1886	0.78
1887	0.955
1888	1.009
1889	1.124
1890	0.906
1891	0.971
1892	0.925
1893	0.745
1894	0.893
1895	0.923
1896	0.907
1897	1.063
1898	1.283
1899	0.624
1900	1.426
1901	1.483
1902	0.952
1903	1.053
1904	1.293
1905	1.055
1906	1.074
1907	1.139
1908	1.083
1909	1.037
1910	0.769
1911	1.119
1912	1.038
1913	1.005
1914	1.13
1915	1.076
1916	0.771
1917	1.206
1918	1.06
1919	0.956
1920	1.016
1921	0.857
1922	1.14
1923	0.977
1924	0.868
1925	1.062
1926	1.045
1927	0.98
1928	0.945
1929	1.224
1930	1.374
1931	1.403
1932	1.385
1933	1.448
1934	1.021
1935	1.121
1936	0.976
1937	1.21
1938	1.368
1939	1.26
1940	1.65
1941	1.524
1942	1.186
1943	1.107
1944	1.542
1945	1.646
1946	1.192
1947	0.925
1948	1.644
1949	1.253
1950	1.31
1951	0.891
1952	0.871
1953	0.79
1954	0.74
1955	1.044
1956	0.733
1957	0.7
1958	1.12
1959	0.558
1960	0.846
1961	0.766
1962	0.661
1963	1.011
1964	0.906
1965	0.955
1966	1.232
1967	1.232
1968	0.897
1969	0.882
1970	0.994
1971	0.85
1972	0.555
1973	0.529
1974	0.453
1975	0.602
1976	0.571
1977	1.068
1978	0.479
1979	0.818
1980	0.591
1981	0.831
1982	0.44
1983	0.554
1984	0.776
1985	1.061
1986	0.927
1987	1.135
1988	1.059
1989	0.805
1990	1.105
1991	0.371
1992	0.554