# northamerica_usa_co543 - Milner Pass - 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.
#
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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/3377
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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_co543 - Milner Pass - 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: Milner Pass
#	Location:
#	Country: United States
#	Northernmost_Latitude: 40.42
#	Southernmost_Latitude: 40.42
#	Easternmost_Longitude: -105.8
#	Westernmost_Longitude: -105.8
#	Elevation: 3413 m
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# Data_Collection
#	Collection_Name: northamerica_usa_co543B
#	Earliest_Year: 1702
#	Most_Recent_Year: 1987
#	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":"5.90548775274","T2":"18.8997109133","M1":"0.0219006115353","M2":"0.290466717401"}}
#--------------------
# Species
#	Species_Name: Engelmann spruce
#	Species_Code: PCEN
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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
1702	0.674
1703	0.643
1704	0.661
1705	0.661
1706	0.674
1707	0.585
1708	0.629
1709	0.932
1710	0.959
1711	0.862
1712	1.003
1713	0.913
1714	0.866
1715	0.931
1716	0.833
1717	1.091
1718	0.914
1719	0.913
1720	0.96
1721	1.054
1722	0.958
1723	0.861
1724	1.115
1725	1.036
1726	1.058
1727	1.106
1728	1.013
1729	0.957
1730	0.939
1731	0.992
1732	0.968
1733	0.994
1734	1.129
1735	1.054
1736	0.995
1737	1.113
1738	1.107
1739	1.301
1740	1.0
1741	0.974
1742	0.93
1743	1.005
1744	1.126
1745	1.119
1746	1.166
1747	1.164
1748	0.937
1749	1.034
1750	1.305
1751	1.302
1752	1.256
1753	1.386
1754	1.119
1755	1.21
1756	1.119
1757	1.332
1758	0.985
1759	1.298
1760	1.105
1761	0.834
1762	1.263
1763	0.94
1764	0.942
1765	1.161
1766	0.895
1767	1.107
1768	0.987
1769	1.048
1770	0.931
1771	1.039
1772	1.062
1773	1.082
1774	1.194
1775	1.194
1776	1.09
1777	1.083
1778	1.0
1779	0.885
1780	1.312
1781	1.081
1782	0.905
1783	1.057
1784	1.225
1785	1.139
1786	1.091
1787	1.166
1788	1.351
1789	1.04
1790	0.903
1791	0.78
1792	0.996
1793	0.985
1794	0.99
1795	1.045
1796	0.993
1797	1.088
1798	1.262
1799	1.12
1800	1.093
1801	1.171
1802	1.2
1803	1.041
1804	1.018
1805	0.997
1806	0.919
1807	0.989
1808	0.968
1809	0.809
1810	0.78
1811	0.881
1812	0.987
1813	0.87
1814	0.821
1815	0.86
1816	0.984
1817	0.966
1818	0.89
1819	0.971
1820	0.862
1821	0.896
1822	0.903
1823	0.879
1824	0.876
1825	0.96
1826	0.996
1827	1.109
1828	1.033
1829	1.122
1830	1.113
1831	1.088
1832	0.974
1833	1.152
1834	1.038
1835	0.824
1836	0.663
1837	0.99
1838	0.867
1839	0.756
1840	0.796
1841	0.862
1842	0.809
1843	0.819
1844	0.853
1845	0.573
1846	0.673
1847	0.568
1848	0.657
1849	0.744
1850	0.744
1851	0.589
1852	0.609
1853	0.603
1854	0.739
1855	0.751
1856	1.061
1857	0.836
1858	0.812
1859	1.126
1860	1.086
1861	1.191
1862	0.967
1863	1.055
1864	0.871
1865	0.755
1866	0.946
1867	1.072
1868	0.893
1869	0.902
1870	0.981
1871	1.036
1872	0.64
1873	0.985
1874	1.064
1875	0.746
1876	1.156
1877	1.007
1878	0.994
1879	0.888
1880	0.739
1881	1.111
1882	0.754
1883	0.777
1884	0.878
1885	0.989
1886	1.204
1887	0.906
1888	0.997
1889	0.98
1890	0.91
1891	0.943
1892	1.061
1893	0.829
1894	1.046
1895	0.901
1896	1.175
1897	1.177
1898	1.353
1899	0.989
1900	1.205
1901	1.172
1902	0.795
1903	1.037
1904	0.813
1905	0.869
1906	0.651
1907	0.867
1908	0.947
1909	1.118
1910	0.999
1911	0.914
1912	0.999
1913	0.88
1914	0.977
1915	0.876
1916	0.907
1917	1.013
1918	0.999
1919	1.129
1920	0.744
1921	0.911
1922	0.924
1923	0.907
1924	0.829
1925	0.844
1926	0.749
1927	1.014
1928	1.148
1929	1.319
1930	1.179
1931	1.157
1932	1.124
1933	1.114
1934	0.926
1935	1.024
1936	0.997
1937	0.929
1938	1.024
1939	1.261
1940	1.078
1941	0.967
1942	0.93
1943	0.929
1944	0.995
1945	0.994
1946	0.95
1947	1.065
1948	0.957
1949	1.041
1950	0.997
1951	1.315
1952	1.16
1953	1.329
1954	1.149
1955	1.134
1956	1.048
1957	1.111
1958	1.032
1959	1.015
1960	1.024
1961	0.993
1962	0.96
1963	1.209
1964	1.344
1965	1.11
1966	1.197
1967	0.844
1968	0.85
1969	0.79
1970	0.859
1971	0.821
1972	0.833
1973	0.862
1974	1.018
1975	1.059
1976	0.971
1977	1.028
1978	1.058
1979	1.067
1980	0.995
1981	0.881
1982	0.802
1983	0.847
1984	0.932
1985	0.794
1986	0.832
1987	1.03