# northamerica_usa_ca639 - Lundy Lake - 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/3320
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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_ca639 - Lundy Lake - 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: Lundy Lake
#	Location:
#	Country: United States
#	Northernmost_Latitude: 38.08
#	Southernmost_Latitude: 38.08
#	Easternmost_Longitude: -119.38
#	Westernmost_Longitude: -119.38
#	Elevation: 2925 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ca639B
#	Earliest_Year: 1864
#	Most_Recent_Year: 1994
#	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":"4.47608133139","T2":"17.1286904549","M1":"0.0221827634185","M2":"0.42765825801"}}
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# Species
#	Species_Name: limber pine
#	Species_Code: PIFL
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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
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age	trsgi
1864	1.005
1865	0.906
1866	0.878
1867	0.785
1868	0.941
1869	1.281
1870	1.434
1871	1.14
1872	1.306
1873	1.253
1874	1.022
1875	0.963
1876	1.173
1877	1.017
1878	1.056
1879	1.131
1880	0.981
1881	0.935
1882	1.157
1883	1.013
1884	1.09
1885	0.685
1886	1.242
1887	0.958
1888	0.921
1889	1.032
1890	0.91
1891	1.134
1892	1.166
1893	0.956
1894	0.97
1895	1.088
1896	1.08
1897	1.162
1898	1.197
1899	0.865
1900	1.295
1901	1.273
1902	1.077
1903	1.015
1904	1.016
1905	0.834
1906	0.978
1907	1.019
1908	1.312
1909	0.991
1910	0.916
1911	1.124
1912	1.059
1913	0.822
1914	0.952
1915	1.035
1916	0.836
1917	0.994
1918	0.987
1919	1.228
1920	1.1
1921	0.965
1922	1.046
1923	0.838
1924	0.89
1925	1.102
1926	1.128
1927	1.072
1928	1.102
1929	0.816
1930	0.689
1931	1.054
1932	0.839
1933	0.561
1934	0.803
1935	0.734
1936	0.627
1937	0.923
1938	0.851
1939	1.036
1940	0.824
1941	0.632
1942	0.991
1943	1.138
1944	0.792
1945	1.084
1946	1.041
1947	0.998
1948	0.972
1949	0.776
1950	0.966
1951	1.01
1952	0.805
1953	0.762
1954	0.894
1955	1.273
1956	0.857
1957	1.108
1958	0.901
1959	1.168
1960	0.85
1961	1.118
1962	1.051
1963	1.26
1964	1.078
1965	1.251
1966	0.913
1967	1.258
1968	1.226
1969	1.394
1970	1.274
1971	1.2
1972	0.935
1973	1.409
1974	1.465
1975	1.334
1976	1.184
1977	1.486
1978	1.041
1979	1.249
1980	1.152
1981	0.986
1982	1.149
1983	1.18
1984	1.441
1985	1.085
1986	1.044
1987	0.846
1988	1.013
1989	1.032
1990	0.757
1991	0.994
1992	1.017
1993	1.172
1994	0.965