# northamerica_usa_wa076 - Hart's Pass V1 - 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/4135
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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_wa076 - Hart's Pass V1 - 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
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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:
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#	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 V1
#	Location:
#	Country: United States
#	Northernmost_Latitude: 48.68
#	Southernmost_Latitude: 48.68
#	Easternmost_Longitude: -120.65
#	Westernmost_Longitude: -120.65
#	Elevation: 1875 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa076B
#	Earliest_Year: 1865
#	Most_Recent_Year: 1990
#	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":"4.98200569348","T2":"17.9025541375","M1":"0.0222851817454","M2":"0.358024468262"}}
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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
1865	0.918
1866	0.744
1867	0.566
1868	0.552
1869	0.738
1870	0.667
1871	0.667
1872	0.549
1873	0.556
1874	0.746
1875	0.468
1876	0.465
1877	0.637
1878	0.651
1879	0.428
1880	0.347
1881	0.53
1882	0.316
1883	0.304
1884	0.36
1885	0.451
1886	0.594
1887	0.462
1888	0.557
1889	0.655
1890	0.849
1891	0.811
1892	0.685
1893	0.633
1894	0.55
1895	0.778
1896	0.662
1897	0.807
1898	0.965
1899	0.825
1900	0.973
1901	0.866
1902	0.856
1903	0.897
1904	0.95
1905	0.902
1906	1.172
1907	1.068
1908	1.18
1909	1.002
1910	0.975
1911	1.094
1912	1.038
1913	1.14
1914	1.313
1915	1.329
1916	0.934
1917	1.071
1918	0.988
1919	1.109
1920	1.243
1921	1.053
1922	1.189
1923	1.087
1924	1.118
1925	1.192
1926	1.247
1927	1.232
1928	1.296
1929	1.249
1930	1.17
1931	1.13
1932	1.061
1933	1.082
1934	1.023
1935	1.078
1936	1.193
1937	1.185
1938	1.172
1939	1.152
1940	1.263
1941	1.299
1942	1.267
1943	1.038
1944	1.404
1945	1.374
1946	1.102
1947	1.196
1948	1.288
1949	1.132
1950	1.141
1951	0.974
1952	1.209
1953	1.135
1954	1.051
1955	1.141
1956	0.668
1957	1.056
1958	1.382
1959	1.12
1960	1.337
1961	1.004
1962	0.972
1963	0.949
1964	1.007
1965	0.998
1966	1.02
1967	1.021
1968	0.824
1969	0.767
1970	0.92
1971	0.878
1972	0.791
1973	1.156
1974	0.85
1975	0.979
1976	0.828
1977	0.939
1978	0.859
1979	0.895
1980	0.776
1981	0.94
1982	0.687
1983	0.62
1984	0.884
1985	0.737
1986	0.619
1987	0.695
1988	0.734
1989	0.597
1990	0.848