# northamerica_usa_wa068 - Hart's Pass R1 - Breitenmoser Tree Ring Chronology Data
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#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
#-----------------------------------------------------------------------
# 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/4132
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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_wa068 - Hart's Pass R1 - 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 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.
#--------------------
#	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 R1
#	Location:
#	Country: United States
#	Northernmost_Latitude: 48.68
#	Southernmost_Latitude: 48.68
#	Easternmost_Longitude: -120.63
#	Westernmost_Longitude: -120.63
#	Elevation: 2050 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa068B
#	Earliest_Year: 1740
#	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":"3.40837474396","T2":"15.1187184959","M1":"0.0227281614221","M2":"0.471039532395"}}
#--------------------
# Species
#	Species_Name: whitebark pine
#	Species_Code: PIAL
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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
1740	0.874
1741	0.895
1742	0.847
1743	0.925
1744	0.969
1745	0.932
1746	0.91
1747	1.333
1748	1.194
1749	1.192
1750	1.155
1751	1.199
1752	0.915
1753	1.065
1754	0.947
1755	0.742
1756	1.031
1757	0.94
1758	1.003
1759	1.092
1760	1.072
1761	1.143
1762	0.95
1763	1.129
1764	0.917
1765	0.813
1766	0.989
1767	0.957
1768	0.829
1769	0.92
1770	0.892
1771	1.116
1772	1.045
1773	1.145
1774	1.151
1775	1.099
1776	1.044
1777	1.406
1778	1.157
1779	1.057
1780	1.027
1781	0.908
1782	0.907
1783	0.972
1784	1.098
1785	1.041
1786	1.232
1787	1.084
1788	1.32
1789	1.255
1790	1.361
1791	1.391
1792	1.424
1793	1.573
1794	1.521
1795	1.369
1796	1.499
1797	1.104
1798	1.28
1799	0.917
1800	1.129
1801	0.876
1802	0.842
1803	0.951
1804	0.899
1805	0.905
1806	0.839
1807	0.742
1808	0.977
1809	0.819
1810	0.679
1811	0.752
1812	0.557
1813	0.586
1814	0.691
1815	0.667
1816	0.647
1817	0.812
1818	0.618
1819	0.506
1820	0.49
1821	0.404
1822	0.434
1823	0.422
1824	0.394
1825	0.605
1826	0.789
1827	0.781
1828	0.889
1829	1.192
1830	1.124
1831	1.125
1832	0.917
1833	1.054
1834	1.186
1835	0.925
1836	1.075
1837	1.014
1838	0.645
1839	0.959
1840	0.669
1841	0.688
1842	0.798
1843	0.997
1844	0.661
1845	0.857
1846	0.951
1847	0.754
1848	0.883
1849	0.872
1850	0.781
1851	0.9
1852	1.072
1853	1.173
1854	1.081
1855	1.286
1856	1.101
1857	1.331
1858	1.196
1859	1.299
1860	1.06
1861	1.061
1862	0.84
1863	1.162
1864	1.062
1865	1.13
1866	1.013
1867	0.905
1868	0.95
1869	1.002
1870	1.004
1871	1.128
1872	1.19
1873	1.235
1874	1.155
1875	1.19
1876	1.222
1877	1.206
1878	1.144
1879	1.251
1880	0.86
1881	0.829
1882	0.949
1883	0.597
1884	0.528
1885	0.47
1886	0.698
1887	0.716
1888	0.664
1889	0.738
1890	0.831
1891	0.967
1892	0.798
1893	0.746
1894	0.675
1895	0.731
1896	0.899
1897	0.845
1898	1.344
1899	0.977
1900	0.986
1901	1.135
1902	0.907
1903	1.175
1904	1.256
1905	1.019
1906	1.059
1907	1.006
1908	1.085
1909	1.038
1910	1.165
1911	1.083
1912	1.081
1913	1.389
1914	1.263
1915	0.959
1916	1.106
1917	0.876
1918	0.982
1919	1.029
1920	0.902
1921	0.976
1922	0.985
1923	1.015
1924	1.02
1925	1.006
1926	0.936
1927	0.935
1928	1.091
1929	1.056
1930	0.911
1931	1.188
1932	0.947
1933	1.056
1934	0.966
1935	0.993
1936	1.185
1937	0.95
1938	1.193
1939	0.985
1940	0.973
1941	1.067
1942	1.024
1943	1.084
1944	1.152
1945	1.268
1946	1.012
1947	1.306
1948	1.472
1949	1.467
1950	1.217
1951	0.91
1952	1.274
1953	1.096
1954	1.078
1955	1.218
1956	0.805
1957	1.246
1958	1.323
1959	1.034
1960	1.025
1961	1.054
1962	0.774
1963	1.195
1964	1.249
1965	1.312
1966	1.055
1967	0.975
1968	0.827
1969	0.794
1970	1.065
1971	0.84
1972	0.704
1973	0.767
1974	0.992
1975	0.9
1976	1.007
1977	1.168
1978	1.033
1979	0.973
1980	0.823
1981	1.035
1982	0.862
1983	0.988
1984	0.868
1985	0.651
1986	0.683
1987	0.809
1988	0.664
1989	0.619
1990	0.638