# northamerica_usa_co588 - Platt Bradbury - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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/5323
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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
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# Title
#	Study_Name: northamerica_usa_co588 - Platt Bradbury - Breitenmoser Tree Ring Chronology Data
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# 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: Platt Bradbury
#	Location:
#	Country: United States
#	Northernmost_Latitude: 37.47
#	Southernmost_Latitude: 37.47
#	Easternmost_Longitude: -106.3
#	Westernmost_Longitude: -106.3
#	Elevation: 2835 m
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# Data_Collection
#	Collection_Name: northamerica_usa_co588B
#	Earliest_Year: 1755
#	Most_Recent_Year: 2004
#	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":"4.20816457463","T2":"15.4413424958","M1":"0.0231763614612","M2":"0.519766313614"}}
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# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
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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
1755	0.94
1756	1.133
1757	1.348
1758	1.159
1759	1.119
1760	0.944
1761	1.228
1762	1.237
1763	0.661
1764	0.747
1765	1.343
1766	1.342
1767	0.804
1768	1.034
1769	0.937
1770	1.016
1771	1.721
1772	0.837
1773	0.456
1774	0.959
1775	0.634
1776	0.962
1777	0.584
1778	0.621
1779	0.658
1780	0.313
1781	0.312
1782	0.644
1783	1.091
1784	1.075
1785	1.241
1786	0.885
1787	1.054
1788	0.574
1789	0.399
1790	1.401
1791	0.824
1792	0.758
1793	0.96
1794	1.0
1795	0.882
1796	0.824
1797	0.959
1798	0.763
1799	0.967
1800	0.844
1801	0.966
1802	0.585
1803	0.858
1804	0.943
1805	0.787
1806	0.683
1807	0.916
1808	0.924
1809	0.734
1810	1.207
1811	1.137
1812	1.223
1813	1.521
1814	1.79
1815	1.686
1816	2.463
1817	1.288
1818	0.389
1819	0.79
1820	0.897
1821	1.185
1822	0.661
1823	0.684
1824	0.673
1825	0.92
1826	0.702
1827	0.783
1828	1.497
1829	1.002
1830	0.946
1831	1.961
1832	1.75
1833	1.273
1834	0.954
1835	1.797
1836	1.122
1837	1.39
1838	1.709
1839	1.395
1840	1.583
1841	1.461
1842	0.972
1843	0.989
1844	0.864
1845	0.953
1846	0.736
1847	0.328
1848	0.886
1849	0.733
1850	0.854
1851	0.296
1852	0.66
1853	1.028
1854	1.053
1855	0.987
1856	0.807
1857	0.9
1858	1.118
1859	1.007
1860	1.175
1861	0.367
1862	0.832
1863	0.944
1864	0.721
1865	0.825
1866	0.879
1867	1.143
1868	1.011
1869	1.285
1870	0.761
1871	0.775
1872	0.61
1873	0.786
1874	0.648
1875	0.467
1876	0.743
1877	0.871
1878	0.604
1879	0.647
1880	0.679
1881	0.478
1882	0.927
1883	0.768
1884	1.028
1885	1.013
1886	0.935
1887	1.111
1888	0.851
1889	1.066
1890	0.746
1891	0.939
1892	0.873
1893	0.68
1894	0.81
1895	1.034
1896	0.69
1897	1.113
1898	1.065
1899	0.424
1900	0.883
1901	0.677
1902	0.231
1903	1.127
1904	0.546
1905	0.814
1906	1.093
1907	2.021
1908	0.924
1909	1.25
1910	1.023
1911	1.331
1912	1.714
1913	0.92
1914	1.145
1915	1.018
1916	0.863
1917	1.05
1918	0.587
1919	1.226
1920	0.932
1921	1.171
1922	0.895
1923	0.838
1924	1.302
1925	1.155
1926	1.279
1927	0.905
1928	1.256
1929	0.841
1930	0.353
1931	0.942
1932	0.777
1933	0.99
1934	0.693
1935	1.047
1936	0.863
1937	1.412
1938	1.291
1939	1.013
1940	0.718
1941	1.301
1942	1.097
1943	0.493
1944	1.192
1945	0.888
1946	0.737
1947	1.211
1948	0.981
1949	1.05
1950	0.428
1951	0.291
1952	0.798
1953	1.253
1954	0.33
1955	0.441
1956	0.486
1957	1.143
1958	0.99
1959	0.522
1960	0.799
1961	0.709
1962	0.975
1963	0.499
1964	0.861
1965	1.161
1966	1.018
1967	1.332
1968	1.64
1969	1.772
1970	1.506
1971	0.966
1972	0.52
1973	1.287
1974	0.5
1975	1.189
1976	0.997
1977	0.279
1978	0.867
1979	1.009
1980	0.908
1981	0.561
1982	0.849
1983	1.616
1984	1.178
1985	1.644
1986	1.286
1987	1.106
1988	1.009
1989	0.781
1990	0.875
1991	1.034
1992	1.275
1993	0.96
1994	1.045
1995	1.123
1996	0.541
1997	0.945
1998	0.955
1999	1.489
2000	1.045
2001	1.408
2002	0.47
2003	0.429
2004	0.928