# northamerica_usa_ne005 - Snake River - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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/5340
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_usa_ne005 - Snake River - Breitenmoser Tree Ring Chronology Data
#--------------------
# 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 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.
#--------------------
#	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: Snake River
#	Location:
#	Country: United States
#	Northernmost_Latitude: 42.7
#	Southernmost_Latitude: 42.7
#	Easternmost_Longitude: -100.87
#	Westernmost_Longitude: -100.87
#	Elevation: 810 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ne005B
#	Earliest_Year: 1796
#	Most_Recent_Year: 1998
#	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":"4.3852499603","T2":"16.4585774054","M1":"0.0230934392041","M2":"0.450472837207"}}
#--------------------
# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
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# Chronology:
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# Variables
#
# 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)
#
##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
1796	0.823
1797	0.729
1798	0.729
1799	0.732
1800	0.837
1801	0.886
1802	0.99
1803	1.234
1804	0.36
1805	0.558
1806	0.714
1807	0.86
1808	0.615
1809	0.773
1810	0.824
1811	0.972
1812	0.867
1813	1.593
1814	1.213
1815	1.206
1816	1.223
1817	0.678
1818	0.94
1819	0.739
1820	0.758
1821	0.864
1822	0.684
1823	0.763
1824	0.507
1825	0.879
1826	0.771
1827	0.875
1828	1.227
1829	1.101
1830	1.619
1831	1.048
1832	1.218
1833	1.831
1834	1.857
1835	1.252
1836	1.513
1837	1.314
1838	1.192
1839	1.458
1840	1.186
1841	0.842
1842	0.94
1843	0.931
1844	1.445
1845	0.99
1846	1.035
1847	0.925
1848	0.566
1849	0.895
1850	0.967
1851	1.138
1852	1.232
1853	1.162
1854	1.279
1855	0.958
1856	0.978
1857	0.793
1858	1.107
1859	0.57
1860	0.678
1861	0.659
1862	0.742
1863	0.673
1864	0.285
1865	0.555
1866	0.668
1867	0.524
1868	0.667
1869	0.701
1870	0.796
1871	1.164
1872	1.302
1873	0.918
1874	0.676
1875	0.865
1876	0.641
1877	0.822
1878	0.999
1879	0.988
1880	0.61
1881	1.097
1882	1.029
1883	0.834
1884	1.09
1885	1.386
1886	1.412
1887	1.21
1888	1.324
1889	1.081
1890	0.847
1891	1.09
1892	1.193
1893	0.911
1894	0.854
1895	0.446
1896	0.492
1897	0.744
1898	0.815
1899	0.6
1900	0.712
1901	0.767
1902	0.924
1903	1.832
1904	1.368
1905	1.34
1906	1.372
1907	1.542
1908	1.26
1909	1.48
1910	1.28
1911	0.878
1912	1.16
1913	1.16
1914	1.01
1915	1.413
1916	1.258
1917	0.825
1918	1.265
1919	0.89
1920	0.92
1921	1.109
1922	1.444
1923	1.165
1924	1.14
1925	0.951
1926	0.489
1927	0.933
1928	1.025
1929	0.918
1930	1.301
1931	1.489
1932	1.373
1933	0.98
1934	0.491
1935	1.076
1936	0.732
1937	0.634
1938	1.257
1939	0.649
1940	0.449
1941	0.937
1942	1.012
1943	0.851
1944	1.206
1945	1.329
1946	1.142
1947	1.411
1948	1.137
1949	1.39
1950	1.06
1951	1.356
1952	1.362
1953	1.185
1954	1.099
1955	1.076
1956	0.674
1957	1.146
1958	0.971
1959	0.447
1960	0.821
1961	0.554
1962	0.846
1963	0.916
1964	0.855
1965	0.593
1966	0.921
1967	1.093
1968	0.741
1969	0.958
1970	0.847
1971	0.816
1972	1.342
1973	0.979
1974	0.825
1975	0.819
1976	0.502
1977	0.915
1978	0.813
1979	0.617
1980	0.924
1981	0.742
1982	1.336
1983	1.069
1984	1.484
1985	0.563
1986	0.807
1987	1.095
1988	1.133
1989	0.356
1990	0.876
1991	0.825
1992	0.844
1993	1.006
1994	0.618
1995	1.016
1996	0.905
1997	0.823
1998	1.113