# northamerica_usa_wa077 - Hart's Pass V2 - 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/4137
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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_wa077 - Hart's Pass V2 - 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: Hart's Pass V2
#	Location:
#	Country: United States
#	Northernmost_Latitude: 48.75
#	Southernmost_Latitude: 48.75
#	Easternmost_Longitude: -120.63
#	Westernmost_Longitude: -120.63
#	Elevation: 1825 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa077B
#	Earliest_Year: 1736
#	Most_Recent_Year: 1991
#	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":"6.21113952688","T2":"17.711319919","M1":"0.0222814837527","M2":"0.364794113043"}}
#--------------------
# Species
#	Species_Name: subalpine fir
#	Species_Code: ABLA
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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
1736	1.322
1737	0.951
1738	0.952
1739	0.988
1740	0.912
1741	0.895
1742	0.684
1743	0.787
1744	0.771
1745	0.869
1746	0.742
1747	0.81
1748	0.874
1749	0.774
1750	0.879
1751	0.871
1752	0.645
1753	0.805
1754	0.625
1755	0.572
1756	0.812
1757	0.799
1758	0.713
1759	0.738
1760	0.672
1761	0.717
1762	0.805
1763	0.861
1764	0.828
1765	0.773
1766	0.857
1767	0.938
1768	0.826
1769	0.871
1770	0.77
1771	0.849
1772	0.684
1773	0.686
1774	0.701
1775	0.56
1776	0.75
1777	0.816
1778	0.741
1779	0.707
1780	0.839
1781	0.749
1782	0.646
1783	0.975
1784	0.894
1785	0.922
1786	0.934
1787	0.836
1788	0.89
1789	0.748
1790	0.846
1791	0.688
1792	0.855
1793	0.927
1794	1.06
1795	0.955
1796	1.049
1797	0.856
1798	0.972
1799	0.891
1800	0.877
1801	0.804
1802	0.896
1803	1.157
1804	1.009
1805	0.971
1806	0.768
1807	1.118
1808	1.001
1809	1.009
1810	0.671
1811	1.03
1812	0.829
1813	0.903
1814	0.836
1815	0.82
1816	0.821
1817	1.027
1818	0.814
1819	0.749
1820	0.813
1821	0.784
1822	1.047
1823	0.955
1824	0.764
1825	1.004
1826	0.918
1827	0.939
1828	0.84
1829	0.974
1830	0.857
1831	1.002
1832	0.564
1833	0.935
1834	0.924
1835	0.929
1836	0.851
1837	0.965
1838	0.744
1839	1.136
1840	0.955
1841	0.9
1842	1.07
1843	1.058
1844	0.988
1845	0.852
1846	0.99
1847	0.847
1848	1.191
1849	1.065
1850	1.013
1851	1.212
1852	1.086
1853	1.021
1854	0.978
1855	1.214
1856	0.96
1857	1.069
1858	0.936
1859	1.121
1860	0.857
1861	0.903
1862	0.79
1863	1.248
1864	0.798
1865	1.196
1866	0.795
1867	0.765
1868	0.941
1869	1.079
1870	0.971
1871	0.981
1872	1.009
1873	1.249
1874	1.214
1875	1.319
1876	0.98
1877	1.098
1878	1.062
1879	0.931
1880	0.891
1881	1.056
1882	1.023
1883	1.049
1884	0.835
1885	1.051
1886	1.195
1887	0.989
1888	1.031
1889	1.102
1890	1.214
1891	1.403
1892	1.14
1893	0.937
1894	0.957
1895	0.985
1896	0.984
1897	0.929
1898	1.147
1899	1.011
1900	1.102
1901	1.256
1902	1.228
1903	1.242
1904	1.35
1905	1.292
1906	1.323
1907	1.354
1908	1.629
1909	1.15
1910	1.23
1911	1.401
1912	1.133
1913	1.265
1914	1.43
1915	1.328
1916	1.18
1917	1.414
1918	1.408
1919	1.413
1920	1.405
1921	1.263
1922	1.337
1923	1.32
1924	1.225
1925	0.802
1926	1.081
1927	1.202
1928	1.233
1929	1.213
1930	1.392
1931	1.326
1932	1.212
1933	1.281
1934	1.118
1935	1.32
1936	1.257
1937	1.34
1938	1.349
1939	1.174
1940	1.296
1941	1.218
1942	1.28
1943	0.789
1944	1.372
1945	1.392
1946	1.049
1947	1.13
1948	1.147
1949	1.025
1950	0.998
1951	0.691
1952	0.903
1953	0.859
1954	0.77
1955	0.939
1956	0.323
1957	0.681
1958	1.023
1959	0.823
1960	0.984
1961	0.701
1962	0.585
1963	0.626
1964	0.713
1965	0.71
1966	0.677
1967	0.661
1968	0.582
1969	0.553
1970	0.725
1971	0.624
1972	0.403
1973	0.585
1974	0.532
1975	0.723
1976	0.705
1977	0.826
1978	0.768
1979	0.709
1980	0.638
1981	0.866
1982	0.736
1983	0.575
1984	0.913
1985	0.791
1986	0.671
1987	0.796
1988	0.922
1989	0.399
1990	0.92
1991	0.566