# northamerica_usa_or053 - Skookum Butte - 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/4783
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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_or053 - Skookum Butte - 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: Skookum Butte
#	Location:
#	Country: United States
#	Northernmost_Latitude: 43.23
#	Southernmost_Latitude: 43.23
#	Easternmost_Longitude: -121.65
#	Westernmost_Longitude: -121.65
#	Elevation: 1670 m
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# Data_Collection
#	Collection_Name: northamerica_usa_or053B
#	Earliest_Year: 1845
#	Most_Recent_Year: 1995
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"3.22196011749","T2":"14.8516110008","M1":"0.0229976392689","M2":"0.474905562248"}}
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# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
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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
1845	0.133
1846	0.525
1847	0.639
1848	0.72
1849	0.867
1850	1.301
1851	1.318
1852	1.048
1853	1.203
1854	1.315
1855	1.363
1856	1.076
1857	1.115
1858	1.254
1859	1.037
1860	1.233
1861	1.16
1862	1.21
1863	1.239
1864	0.971
1865	1.15
1866	1.308
1867	1.085
1868	1.061
1869	1.019
1870	1.06
1871	1.016
1872	0.932
1873	1.144
1874	1.185
1875	1.21
1876	1.105
1877	1.205
1878	1.068
1879	1.024
1880	0.895
1881	1.28
1882	1.18
1883	0.999
1884	1.034
1885	1.139
1886	0.936
1887	1.008
1888	1.097
1889	1.1
1890	0.793
1891	0.956
1892	0.961
1893	0.986
1894	1.2
1895	1.204
1896	1.068
1897	1.213
1898	1.166
1899	0.917
1900	1.36
1901	1.347
1902	1.162
1903	1.223
1904	1.151
1905	1.287
1906	1.134
1907	1.213
1908	1.258
1909	1.124
1910	1.043
1911	1.138
1912	1.159
1913	1.289
1914	1.257
1915	1.295
1916	1.166
1917	0.923
1918	1.121
1919	1.111
1920	0.886
1921	1.03
1922	0.79
1923	1.014
1924	0.838
1925	0.872
1926	0.951
1927	0.92
1928	0.892
1929	0.745
1930	0.845
1931	0.851
1932	0.857
1933	0.761
1934	0.985
1935	0.694
1936	0.885
1937	0.813
1938	0.854
1939	0.874
1940	0.784
1941	0.858
1942	0.906
1943	0.919
1944	1.05
1945	0.966
1946	0.953
1947	1.052
1948	0.79
1949	0.79
1950	0.718
1951	0.774
1952	0.693
1953	0.746
1954	0.976
1955	0.953
1956	0.855
1957	0.879
1958	0.903
1959	1.017
1960	1.105
1961	0.856
1962	0.801
1963	0.967
1964	0.789
1965	0.659
1966	0.693
1967	0.488
1968	0.35
1969	0.278
1970	0.359
1971	0.409
1972	0.377
1973	0.417
1974	0.482
1975	0.632
1976	0.892
1977	0.892
1978	0.979
1979	0.983
1980	1.071
1981	1.138
1982	1.099
1983	1.337
1984	1.409
1985	1.227
1986	1.412
1987	1.184
1988	1.307
1989	1.374
1990	1.371
1991	1.084
1992	1.191
1993	1.281
1994	1.187
1995	1.376