# northamerica_usa_wa122 - Klahhane Ridge 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/4143
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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_wa122 - Klahhane Ridge 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: Klahhane Ridge Low
#	Location:
#	Country: United States
#	Northernmost_Latitude: 48.0
#	Southernmost_Latitude: 48.0
#	Easternmost_Longitude: -123.42
#	Westernmost_Longitude: -123.42
#	Elevation: 1375 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa122B
#	Earliest_Year: 1850
#	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":"5.261996983","T2":"15.7920147286","M1":"0.0230023351843","M2":"0.49906013292"}}
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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	0.841
1851	0.845
1852	0.881
1853	0.943
1854	0.874
1855	0.831
1856	0.946
1857	0.948
1858	0.994
1859	0.869
1860	1.056
1861	0.947
1862	0.983
1863	0.983
1864	1.106
1865	1.14
1866	1.064
1867	1.038
1868	1.086
1869	0.938
1870	0.925
1871	0.939
1872	1.11
1873	1.118
1874	1.106
1875	1.052
1876	0.739
1877	1.028
1878	1.113
1879	1.151
1880	0.952
1881	1.062
1882	1.266
1883	1.049
1884	1.088
1885	1.063
1886	1.254
1887	0.929
1888	0.996
1889	1.021
1890	1.101
1891	1.194
1892	1.006
1893	0.979
1894	1.004
1895	0.938
1896	0.815
1897	0.778
1898	0.894
1899	0.76
1900	0.945
1901	1.08
1902	0.939
1903	1.039
1904	1.199
1905	1.096
1906	1.016
1907	1.176
1908	1.229
1909	0.908
1910	0.859
1911	1.089
1912	1.07
1913	1.164
1914	1.175
1915	1.104
1916	0.972
1917	0.935
1918	0.889
1919	1.091
1920	0.856
1921	0.974
1922	0.896
1923	0.84
1924	0.752
1925	0.869
1926	0.711
1927	0.797
1928	0.834
1929	0.877
1930	0.787
1931	0.782
1932	0.773
1933	0.876
1934	0.746
1935	0.927
1936	0.696
1937	0.781
1938	0.711
1939	0.8
1940	0.837
1941	0.961
1942	0.953
1943	0.746
1944	1.072
1945	0.831
1946	0.887
1947	0.883
1948	1.068
1949	1.194
1950	1.126
1951	0.974
1952	0.997
1953	0.717
1954	1.08
1955	1.464
1956	1.085
1957	1.106
1958	1.171
1959	0.717
1960	1.002
1961	0.882
1962	0.856
1963	0.992
1964	1.226
1965	1.168
1966	1.177
1967	1.198
1968	0.915
1969	1.143
1970	1.082
1971	1.036
1972	1.178
1973	1.026
1974	0.932
1975	0.848
1976	0.935
1977	1.181
1978	0.849
1979	1.019
1980	1.081
1981	1.351
1982	0.949
1983	0.966
1984	1.287
1985	1.161
1986	0.85
1987	1.077
1988	0.772
1989	0.864
1990	1.124