# northamerica_usa_wa080 - Hart's Pass S1 - 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/4134
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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_wa080 - Hart's Pass S1 - Breitenmoser Tree Ring Chronology Data
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# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
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# 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: Hart's Pass S1
#	Location:
#	Country: United States
#	Northernmost_Latitude: 48.72
#	Southernmost_Latitude: 48.72
#	Easternmost_Longitude: -120.65
#	Westernmost_Longitude: -120.65
#	Elevation: 1825 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa080B
#	Earliest_Year: 1851
#	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":"5.30559328047","T2":"17.7349033658","M1":"0.0227685177214","M2":"0.401298607757"}}
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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
1851	0.989
1852	0.988
1853	1.003
1854	0.953
1855	1.031
1856	1.121
1857	1.3
1858	1.11
1859	1.331
1860	1.013
1861	1.257
1862	1.051
1863	1.543
1864	1.039
1865	1.317
1866	1.023
1867	0.923
1868	1.082
1869	0.973
1870	1.038
1871	1.137
1872	1.159
1873	1.308
1874	1.236
1875	1.293
1876	1.024
1877	1.281
1878	1.207
1879	1.109
1880	0.973
1881	1.264
1882	1.326
1883	1.165
1884	0.95
1885	1.338
1886	1.483
1887	1.068
1888	1.173
1889	1.055
1890	1.019
1891	1.092
1892	0.89
1893	0.856
1894	0.856
1895	1.029
1896	0.967
1897	1.0
1898	1.061
1899	0.82
1900	1.043
1901	0.997
1902	0.954
1903	1.013
1904	1.182
1905	0.902
1906	1.082
1907	0.979
1908	1.226
1909	0.797
1910	0.891
1911	1.064
1912	1.085
1913	1.09
1914	1.167
1915	1.133
1916	0.914
1917	1.105
1918	1.059
1919	0.976
1920	1.251
1921	1.022
1922	1.169
1923	1.185
1924	1.013
1925	0.711
1926	0.985
1927	1.064
1928	1.157
1929	0.987
1930	1.01
1931	1.045
1932	0.915
1933	1.019
1934	1.043
1935	1.053
1936	1.039
1937	0.972
1938	1.102
1939	0.912
1940	1.007
1941	1.119
1942	1.263
1943	0.963
1944	1.308
1945	1.239
1946	1.049
1947	1.122
1948	1.196
1949	1.124
1950	0.994
1951	0.846
1952	0.997
1953	0.986
1954	1.038
1955	1.253
1956	0.531
1957	0.978
1958	1.228
1959	1.04
1960	1.415
1961	1.001
1962	0.813
1963	1.088
1964	1.167
1965	1.165
1966	1.154
1967	1.046
1968	0.729
1969	0.829
1970	0.83
1971	0.786
1972	0.707
1973	0.839
1974	0.674
1975	0.711
1976	0.811
1977	0.96
1978	0.92
1979	0.897
1980	0.86
1981	1.134
1982	0.725
1983	0.817
1984	1.019
1985	0.611
1986	0.579
1987	0.788
1988	0.881
1989	0.546
1990	0.967
1991	0.452
1992	0.902