# northamerica_usa_sd014 - Lake Herman State Park - 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/3954
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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_sd014 - Lake Herman State Park - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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: Lake Herman State Park
#	Location:
#	Country: United States
#	Northernmost_Latitude: 43.98
#	Southernmost_Latitude: 43.98
#	Easternmost_Longitude: -97.17
#	Westernmost_Longitude: -97.17
#	Elevation: 512 m
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# Data_Collection
#	Collection_Name: northamerica_usa_sd014B
#	Earliest_Year: 1873
#	Most_Recent_Year: 1991
#	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":"3.994191499","T2":"15.6234000511","M1":"0.0231767118177","M2":"0.542837552957"}}
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# Species
#	Species_Name: burr oak
#	Species_Code: QUMA
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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
1873	1.37
1874	1.03
1875	1.42
1876	1.386
1877	1.413
1878	1.118
1879	0.825
1880	1.055
1881	1.342
1882	1.403
1883	1.162
1884	1.626
1885	1.472
1886	0.741
1887	0.9
1888	1.107
1889	0.593
1890	0.645
1891	0.581
1892	0.872
1893	0.502
1894	0.28
1895	0.325
1896	0.805
1897	1.238
1898	1.426
1899	0.893
1900	0.439
1901	1.033
1902	1.032
1903	1.783
1904	1.492
1905	1.268
1906	0.845
1907	1.225
1908	1.269
1909	1.129
1910	0.717
1911	0.443
1912	1.236
1913	1.228
1914	1.099
1915	1.213
1916	1.296
1917	0.888
1918	0.646
1919	1.238
1920	1.178
1921	0.718
1922	1.038
1923	0.635
1924	0.693
1925	0.312
1926	0.231
1927	1.015
1928	0.687
1929	0.946
1930	0.71
1931	0.26
1932	0.671
1933	0.503
1934	0.315
1935	0.712
1936	0.567
1937	0.471
1938	0.495
1939	0.351
1940	0.388
1941	0.533
1942	1.115
1943	0.889
1944	1.236
1945	1.257
1946	0.706
1947	1.353
1948	1.134
1949	1.037
1950	0.964
1951	1.097
1952	1.028
1953	1.179
1954	0.857
1955	0.558
1956	1.374
1957	1.527
1958	1.075
1959	0.733
1960	1.154
1961	1.084
1962	0.89
1963	0.599
1964	0.988
1965	1.228
1966	0.91
1967	1.047
1968	1.041
1969	1.16
1970	1.321
1971	1.106
1972	1.644
1973	1.068
1974	1.177
1975	1.151
1976	0.743
1977	0.894
1978	1.384
1979	1.647
1980	1.194
1981	0.916
1982	1.171
1983	1.224
1984	1.167
1985	0.997
1986	1.171
1987	0.938
1988	0.907
1989	0.812
1990	1.134
1991	0.852