# northamerica_usa_nm574 - Cornay Ranch - 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/5292
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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_nm574 - Cornay Ranch - 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: Cornay Ranch
#	Location:
#	Country: United States
#	Northernmost_Latitude: 36.8
#	Southernmost_Latitude: 36.8
#	Easternmost_Longitude: -103.98
#	Westernmost_Longitude: -103.98
#	Elevation: 2020 m
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# Data_Collection
#	Collection_Name: northamerica_usa_nm574B
#	Earliest_Year: 1717
#	Most_Recent_Year: 1998
#	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":"3.03422721653","T2":"14.8207868231","M1":"0.0243858327241","M2":"0.546784350125"}}
#--------------------
# 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)
#
##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
1717	0.632
1718	0.699
1719	0.685
1720	0.869
1721	1.347
1722	1.008
1723	1.114
1724	1.094
1725	0.4
1726	1.123
1727	0.95
1728	0.825
1729	0.648
1730	0.318
1731	1.164
1732	1.039
1733	0.445
1734	1.318
1735	0.525
1736	1.047
1737	0.334
1738	0.257
1739	0.457
1740	1.145
1741	0.899
1742	0.454
1743	1.131
1744	0.788
1745	0.217
1746	1.402
1747	1.88
1748	1.18
1749	1.893
1750	1.06
1751	1.482
1752	1.044
1753	1.378
1754	1.324
1755	1.964
1756	0.557
1757	0.67
1758	1.253
1759	1.47
1760	1.131
1761	1.946
1762	1.344
1763	0.577
1764	1.503
1765	1.048
1766	1.72
1767	1.528
1768	1.495
1769	1.19
1770	0.445
1771	1.41
1772	0.416
1773	0.896
1774	1.385
1775	1.407
1776	1.416
1777	0.939
1778	0.965
1779	1.208
1780	1.029
1781	0.733
1782	0.74
1783	1.332
1784	1.011
1785	1.053
1786	1.231
1787	0.662
1788	0.908
1789	-0.009
1790	0.644
1791	0.369
1792	0.935
1793	0.731
1794	1.058
1795	0.81
1796	0.929
1797	1.041
1798	0.706
1799	0.748
1800	1.315
1801	0.797
1802	1.072
1803	0.838
1804	1.31
1805	0.838
1806	0.766
1807	1.109
1808	0.559
1809	0.514
1810	0.585
1811	0.391
1812	0.817
1813	1.133
1814	1.085
1815	0.603
1816	0.96
1817	1.363
1818	0.406
1819	0.535
1820	0.588
1821	0.416
1822	-0.03
1823	1.299
1824	0.582
1825	1.391
1826	1.486
1827	0.963
1828	1.226
1829	1.215
1830	1.088
1831	0.658
1832	1.063
1833	1.372
1834	0.767
1835	1.097
1836	1.082
1837	0.984
1838	1.316
1839	1.73
1840	1.477
1841	1.133
1842	0.598
1843	0.613
1844	1.472
1845	1.267
1846	0.596
1847	0.958
1848	0.387
1849	1.287
1850	0.977
1851	0.162
1852	0.53
1853	0.707
1854	0.787
1855	0.918
1856	0.446
1857	0.828
1858	1.522
1859	1.18
1860	0.465
1861	0.168
1862	0.497
1863	0.119
1864	0.509
1865	0.552
1866	0.337
1867	0.883
1868	1.067
1869	1.328
1870	0.871
1871	1.022
1872	1.433
1873	1.038
1874	0.58
1875	0.934
1876	0.84
1877	0.888
1878	1.149
1879	0.974
1880	0.143
1881	0.967
1882	1.056
1883	0.529
1884	1.028
1885	0.397
1886	1.123
1887	1.77
1888	0.948
1889	1.095
1890	1.277
1891	1.372
1892	1.159
1893	0.806
1894	0.894
1895	0.996
1896	0.883
1897	1.51
1898	1.324
1899	0.702
1900	1.528
1901	1.326
1902	0.789
1903	0.699
1904	0.657
1905	1.607
1906	0.87
1907	1.646
1908	0.888
1909	1.054
1910	1.207
1911	1.042
1912	1.647
1913	1.295
1914	1.714
1915	2.283
1916	1.306
1917	1.469
1918	1.786
1919	2.247
1920	1.97
1921	2.562
1922	1.471
1923	0.886
1924	1.589
1925	0.905
1926	1.543
1927	0.452
1928	1.534
1929	1.342
1930	1.201
1931	1.478
1932	1.115
1933	0.353
1934	0.272
1935	0.285
1936	0.145
1937	0.553
1938	0.727
1939	0.378
1940	0.551
1941	1.325
1942	1.219
1943	0.866
1944	1.608
1945	1.163
1946	0.885
1947	1.521
1948	1.115
1949	1.543
1950	0.494
1951	0.734
1952	0.406
1953	0.666
1954	0.477
1955	1.214
1956	0.551
1957	0.63
1958	1.075
1959	0.793
1960	0.676
1961	0.953
1962	0.51
1963	-0.034
1964	0.464
1965	0.816
1966	0.289
1967	0.474
1968	0.564
1969	1.318
1970	0.741
1971	0.846
1972	0.279
1973	0.849
1974	0.343
1975	0.457
1976	0.814
1977	0.662
1978	0.697
1979	0.962
1980	1.039
1981	0.653
1982	0.862
1983	1.103
1984	0.829
1985	1.082
1986	1.208
1987	1.299
1988	1.096
1989	0.988
1990	0.854
1991	1.068
1992	0.986
1993	1.157
1994	0.784
1995	0.933
1996	0.674
1997	0.832
1998	0.682