# northamerica_usa_nv049 - Pony Express - 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/4986
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
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# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_usa_nv049 - Pony Express - 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.
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#	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: Pony Express
#	Location:
#	Country: United States
#	Northernmost_Latitude: 39.82
#	Southernmost_Latitude: 39.82
#	Easternmost_Longitude: -114.62
#	Westernmost_Longitude: -114.62
#	Elevation: 2210 m
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# Data_Collection
#	Collection_Name: northamerica_usa_nv049B
#	Earliest_Year: 1723
#	Most_Recent_Year: 1982
#	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":"4.83075929665","T2":"15.9988587087","M1":"0.023133572887","M2":"0.461905685175"}}
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# Species
#	Species_Name: singleleaf pinyon pine
#	Species_Code: PIMO
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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)
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##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
1723	1.268
1724	1.335
1725	1.294
1726	1.367
1727	1.35
1728	1.369
1729	0.145
1730	0.834
1731	1.106
1732	1.018
1733	0.974
1734	0.894
1735	0.432
1736	0.994
1737	1.123
1738	1.275
1739	1.064
1740	1.331
1741	1.118
1742	1.044
1743	0.91
1744	0.73
1745	1.122
1746	1.278
1747	1.207
1748	0.418
1749	0.829
1750	0.891
1751	0.782
1752	0.703
1753	0.847
1754	0.926
1755	0.724
1756	0.603
1757	0.446
1758	0.845
1759	0.72
1760	0.841
1761	1.386
1762	1.09
1763	0.763
1764	0.746
1765	0.399
1766	0.748
1767	0.955
1768	1.014
1769	1.183
1770	1.065
1771	1.143
1772	0.436
1773	0.924
1774	0.891
1775	1.247
1776	1.283
1777	0.451
1778	0.89
1779	0.944
1780	0.998
1781	0.817
1782	0.474
1783	0.694
1784	0.779
1785	0.862
1786	0.938
1787	0.878
1788	0.663
1789	0.801
1790	1.087
1791	1.263
1792	1.313
1793	1.06
1794	0.871
1795	0.548
1796	0.792
1797	0.978
1798	0.543
1799	1.17
1800	0.635
1801	0.897
1802	1.163
1803	1.38
1804	1.417
1805	1.44
1806	0.806
1807	1.313
1808	0.789
1809	0.713
1810	1.281
1811	1.678
1812	1.459
1813	0.668
1814	1.006
1815	1.235
1816	1.593
1817	1.341
1818	1.107
1819	1.403
1820	1.421
1821	1.481
1822	0.788
1823	1.016
1824	0.398
1825	1.047
1826	1.273
1827	1.178
1828	1.156
1829	1.036
1830	1.365
1831	0.853
1832	1.209
1833	1.204
1834	0.746
1835	0.617
1836	0.632
1837	1.156
1838	1.6
1839	1.633
1840	1.147
1841	1.047
1842	0.978
1843	0.453
1844	0.992
1845	1.034
1846	0.586
1847	0.974
1848	0.841
1849	1.224
1850	1.136
1851	0.99
1852	0.7
1853	1.229
1854	1.359
1855	1.038
1856	0.99
1857	1.118
1858	1.241
1859	0.925
1860	0.649
1861	0.799
1862	1.115
1863	0.341
1864	0.639
1865	0.538
1866	1.21
1867	1.133
1868	1.266
1869	1.182
1870	0.87
1871	0.6
1872	0.903
1873	1.06
1874	1.036
1875	1.081
1876	0.986
1877	0.698
1878	1.005
1879	0.647
1880	0.943
1881	0.968
1882	1.007
1883	0.675
1884	1.098
1885	1.434
1886	1.041
1887	0.862
1888	0.842
1889	0.709
1890	1.154
1891	1.366
1892	1.098
1893	0.666
1894	1.1
1895	1.328
1896	0.917
1897	0.551
1898	1.009
1899	0.944
1900	0.677
1901	0.86
1902	0.929
1903	1.062
1904	1.085
1905	1.313
1906	1.348
1907	1.247
1908	1.395
1909	1.087
1910	0.725
1911	1.074
1912	1.316
1913	1.519
1914	1.74
1915	1.308
1916	1.129
1917	1.276
1918	0.877
1919	1.012
1920	1.211
1921	0.826
1922	0.954
1923	1.148
1924	0.512
1925	1.049
1926	1.159
1927	0.444
1928	0.719
1929	1.01
1930	1.188
1931	0.499
1932	1.337
1933	0.825
1934	-0.064
1935	0.771
1936	0.927
1937	1.146
1938	1.046
1939	0.863
1940	1.28
1941	1.433
1942	0.993
1943	1.031
1944	1.118
1945	0.804
1946	1.052
1947	1.379
1948	0.555
1949	0.965
1950	0.982
1951	0.944
1952	0.956
1953	0.837
1954	0.504
1955	0.827
1956	1.28
1957	0.955
1958	0.761
1959	0.594
1960	0.776
1961	0.668
1962	0.789
1963	1.14
1964	0.957
1965	0.709
1966	1.104
1967	1.138
1968	0.788
1969	1.099
1970	0.784
1971	1.037
1972	0.944
1973	1.244
1974	0.915
1975	0.95
1976	0.916
1977	0.915
1978	0.949
1979	1.145
1980	1.154
1981	0.731
1982	1.099