# northamerica_usa_ut521 - Skutumpah Road #1 - 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/3443
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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_ut521 - Skutumpah Road #1 - 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: Skutumpah Road #1
#	Location:
#	Country: United States
#	Northernmost_Latitude: 37.5
#	Southernmost_Latitude: 37.5
#	Easternmost_Longitude: -112.07
#	Westernmost_Longitude: -112.07
#	Elevation: 1800 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ut521B
#	Earliest_Year: 1715
#	Most_Recent_Year: 2000
#	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":"3.82759440636","T2":"16.0099043881","M1":"0.0233732641544","M2":"0.482080694522"}}
#--------------------
# Species
#	Species_Name: pinyon pine
#	Species_Code: PIED
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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
1715	0.652
1716	0.669
1717	0.734
1718	1.263
1719	1.297
1720	1.654
1721	0.744
1722	0.563
1723	1.113
1724	1.393
1725	1.398
1726	1.534
1727	1.239
1728	0.996
1729	0.194
1730	0.67
1731	1.175
1732	1.198
1733	0.961
1734	1.19
1735	0.254
1736	0.387
1737	0.708
1738	1.155
1739	0.601
1740	0.61
1741	0.928
1742	0.397
1743	1.13
1744	1.162
1745	1.191
1746	1.26
1747	1.246
1748	0.408
1749	0.807
1750	0.708
1751	0.703
1752	0.714
1753	0.841
1754	0.715
1755	0.628
1756	0.738
1757	0.744
1758	0.936
1759	0.926
1760	0.936
1761	0.479
1762	0.711
1763	0.518
1764	1.04
1765	1.046
1766	1.563
1767	1.54
1768	1.477
1769	1.477
1770	1.188
1771	1.345
1772	1.264
1773	0.299
1774	0.766
1775	1.358
1776	1.17
1777	0.926
1778	1.012
1779	0.925
1780	0.602
1781	0.957
1782	0.728
1783	1.016
1784	1.37
1785	0.618
1786	1.04
1787	1.517
1788	0.56
1789	0.422
1790	0.454
1791	1.1
1792	1.405
1793	1.483
1794	1.022
1795	1.425
1796	0.997
1797	1.406
1798	1.189
1799	1.302
1800	0.964
1801	0.984
1802	1.211
1803	0.708
1804	1.132
1805	0.904
1806	1.055
1807	1.052
1808	0.664
1809	0.773
1810	1.008
1811	1.404
1812	0.877
1813	0.572
1814	1.262
1815	1.037
1816	1.707
1817	1.246
1818	0.815
1819	1.188
1820	0.3
1821	0.709
1822	0.473
1823	0.776
1824	0.422
1825	0.845
1826	0.988
1827	0.853
1828	1.375
1829	0.823
1830	0.918
1831	0.831
1832	1.284
1833	1.26
1834	1.109
1835	1.377
1836	1.189
1837	1.198
1838	1.292
1839	1.328
1840	1.543
1841	0.99
1842	1.006
1843	1.099
1844	1.305
1845	0.847
1846	1.024
1847	0.309
1848	1.325
1849	1.372
1850	1.36
1851	1.264
1852	1.493
1853	1.528
1854	1.129
1855	1.265
1856	0.805
1857	0.483
1858	0.527
1859	0.589
1860	0.585
1861	0.393
1862	1.232
1863	0.942
1864	0.324
1865	0.926
1866	1.286
1867	1.156
1868	1.498
1869	1.337
1870	0.814
1871	0.47
1872	1.148
1873	0.831
1874	1.206
1875	1.253
1876	0.807
1877	0.883
1878	0.886
1879	0.78
1880	0.788
1881	0.545
1882	0.469
1883	0.244
1884	0.977
1885	1.511
1886	1.243
1887	0.965
1888	1.198
1889	1.6
1890	1.808
1891	1.555
1892	1.418
1893	1.14
1894	0.59
1895	0.972
1896	0.233
1897	1.09
1898	1.106
1899	0.134
1900	0.67
1901	1.241
1902	0.497
1903	1.029
1904	0.486
1905	1.163
1906	1.497
1907	1.652
1908	1.576
1909	1.366
1910	1.689
1911	1.746
1912	1.414
1913	1.322
1914	1.585
1915	1.357
1916	1.484
1917	1.362
1918	1.249
1919	1.046
1920	1.281
1921	1.246
1922	1.161
1923	1.146
1924	0.762
1925	0.685
1926	0.885
1927	0.902
1928	1.11
1929	0.624
1930	0.862
1931	0.977
1932	1.129
1933	1.008
1934	0.853
1935	1.121
1936	0.749
1937	0.807
1938	0.993
1939	0.875
1940	1.053
1941	1.282
1942	1.379
1943	1.487
1944	1.33
1945	1.172
1946	0.75
1947	1.093
1948	1.049
1949	1.299
1950	0.824
1951	0.697
1952	1.152
1953	0.722
1954	1.121
1955	0.876
1956	0.453
1957	0.996
1958	1.031
1959	0.489
1960	0.897
1961	0.781
1962	1.192
1963	0.712
1964	0.756
1965	0.936
1966	0.883
1967	1.081
1968	1.201
1969	1.316
1970	0.843
1971	0.98
1972	0.836
1973	1.043
1974	0.673
1975	1.061
1976	0.957
1977	0.155
1978	0.82
1979	0.962
1980	1.094
1981	0.941
1982	0.816
1983	1.067
1984	0.704
1985	0.868
1986	0.82
1987	0.774
1988	0.852
1989	0.752
1990	0.327
1991	0.589
1992	0.912
1993	0.903
1994	0.799
1995	1.169
1996	0.32
1997	0.84
1998	0.84
1999	0.914
2000	0.415