# northamerica_usa_wa067 - Hart's Pass R1 - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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.
#
#
# 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/4131
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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_wa067 - 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_wa067B
#	Earliest_Year: 1693
#	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":"4.65484954414","T2":"12.2175271891","M1":"0.0232839495471","M2":"0.560293026898"}}
#--------------------
# Species
#	Species_Name: subalpine larch
#	Species_Code: LALY
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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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1693	1.093
1694	0.876
1695	0.779
1696	0.598
1697	0.79
1698	0.864
1699	0.255
1700	0.837
1701	0.805
1702	0.754
1703	0.583
1704	0.645
1705	0.993
1706	0.61
1707	0.365
1708	0.708
1709	0.6
1710	0.87
1711	0.965
1712	0.759
1713	0.407
1714	0.971
1715	0.315
1716	0.638
1717	0.834
1718	0.827
1719	0.825
1720	0.548
1721	0.87
1722	1.086
1723	0.779
1724	1.047
1725	1.122
1726	1.23
1727	1.223
1728	1.119
1729	1.368
1730	1.5
1731	1.03
1732	1.042
1733	1.083
1734	1.48
1735	1.077
1736	0.866
1737	0.768
1738	1.003
1739	1.302
1740	1.38
1741	1.688
1742	0.966
1743	1.14
1744	1.009
1745	1.351
1746	0.836
1747	1.423
1748	1.209
1749	1.16
1750	0.764
1751	0.728
1752	0.337
1753	0.865
1754	0.906
1755	0.666
1756	1.328
1757	0.936
1758	0.777
1759	0.778
1760	0.783
1761	0.836
1762	0.611
1763	0.776
1764	0.957
1765	0.775
1766	0.882
1767	0.989
1768	1.163
1769	1.118
1770	0.992
1771	1.259
1772	0.975
1773	1.118
1774	1.446
1775	0.864
1776	0.941
1777	1.017
1778	0.778
1779	0.776
1780	0.861
1781	1.136
1782	0.958
1783	1.535
1784	0.84
1785	0.854
1786	1.133
1787	1.203
1788	1.229
1789	1.094
1790	1.773
1791	0.969
1792	1.013
1793	0.786
1794	0.949
1795	0.758
1796	0.939
1797	0.811
1798	1.451
1799	0.933
1800	0.887
1801	1.043
1802	1.388
1803	1.363
1804	1.112
1805	0.825
1806	0.722
1807	1.241
1808	1.315
1809	1.28
1810	1.015
1811	1.176
1812	1.252
1813	0.98
1814	0.815
1815	0.826
1816	0.912
1817	1.48
1818	0.808
1819	0.844
1820	0.924
1821	0.814
1822	0.922
1823	0.916
1824	0.318
1825	0.954
1826	1.068
1827	1.083
1828	1.037
1829	1.105
1830	1.339
1831	1.507
1832	0.343
1833	1.122
1834	1.426
1835	1.189
1836	0.839
1837	1.006
1838	0.466
1839	0.878
1840	0.977
1841	1.347
1842	1.259
1843	1.162
1844	0.659
1845	1.216
1846	1.103
1847	1.119
1848	1.204
1849	0.769
1850	1.031
1851	1.327
1852	1.478
1853	0.893
1854	0.683
1855	1.294
1856	0.812
1857	1.103
1858	0.889
1859	1.275
1860	1.172
1861	1.399
1862	1.278
1863	1.686
1864	0.736
1865	0.982
1866	1.072
1867	0.741
1868	1.115
1869	1.081
1870	0.858
1871	1.157
1872	1.677
1873	1.598
1874	1.416
1875	1.364
1876	1.103
1877	0.703
1878	1.139
1879	0.49
1880	0.659
1881	0.775
1882	0.939
1883	0.903
1884	0.89
1885	0.814
1886	0.947
1887	0.976
1888	0.884
1889	0.838
1890	0.622
1891	0.626
1892	0.972
1893	0.613
1894	1.174
1895	0.948
1896	0.907
1897	0.156
1898	0.604
1899	0.623
1900	0.438
1901	0.653
1902	0.541
1903	0.903
1904	0.981
1905	0.562
1906	0.261
1907	0.52
1908	0.853
1909	0.701
1910	0.819
1911	0.75
1912	0.793
1913	0.747
1914	1.027
1915	0.387
1916	0.644
1917	0.987
1918	1.208
1919	1.134
1920	1.033
1921	0.936
1922	1.282
1923	0.954
1924	0.962
1925	0.847
1926	0.518
1927	0.59
1928	0.868
1929	0.813
1930	0.557
1931	0.736
1932	0.876
1933	1.069
1934	1.305
1935	0.882
1936	1.263
1937	1.076
1938	1.163
1939	0.572
1940	1.054
1941	0.901
1942	1.166
1943	1.027
1944	1.213
1945	1.312
1946	0.433
1947	1.007
1948	1.277
1949	1.08
1950	1.496
1951	1.184
1952	0.71
1953	0.821
1954	1.115
1955	1.025
1956	0.636
1957	1.405
1958	1.457
1959	0.815
1960	1.081
1961	1.094
1962	0.71
1963	1.271
1964	1.376
1965	1.407
1966	1.097
1967	1.581
1968	0.875
1969	1.153
1970	1.211
1971	0.648
1972	0.734
1973	0.873
1974	0.886
1975	1.044
1976	0.945
1977	1.269
1978	1.411
1979	1.08
1980	0.673
1981	1.074
1982	1.174
1983	1.23
1984	1.584
1985	1.31
1986	0.954
1987	1.035
1988	0.957
1989	1.015
1990	1.113
1991	0.753