# northamerica_usa_co531 - Ormes Peak - 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.
#
#
# 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/5088
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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_co531 - Ormes Peak - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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: Ormes Peak
#	Location:
#	Country: United States
#	Northernmost_Latitude: 38.95
#	Southernmost_Latitude: 38.95
#	Easternmost_Longitude: -104.95
#	Westernmost_Longitude: -104.95
#	Elevation: 2895 m
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# Data_Collection
#	Collection_Name: northamerica_usa_co531B
#	Earliest_Year: 1738
#	Most_Recent_Year: 1983
#	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":"4.80941133695","T2":"16.850657298","M1":"0.0233002407305","M2":"0.443801325042"}}
#--------------------
# 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
#
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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
1738	0.829
1739	1.092
1740	1.065
1741	0.913
1742	0.48
1743	1.129
1744	1.174
1745	0.959
1746	1.436
1747	1.341
1748	0.653
1749	0.984
1750	0.825
1751	1.015
1752	0.891
1753	0.996
1754	0.865
1755	1.125
1756	0.562
1757	1.084
1758	0.727
1759	0.9
1760	0.974
1761	1.482
1762	1.304
1763	0.998
1764	1.169
1765	1.087
1766	1.281
1767	1.112
1768	1.189
1769	0.961
1770	1.145
1771	1.143
1772	0.943
1773	1.23
1774	1.223
1775	0.777
1776	1.31
1777	1.185
1778	1.12
1779	0.99
1780	0.989
1781	0.709
1782	0.594
1783	0.893
1784	1.06
1785	0.875
1786	0.829
1787	1.09
1788	1.124
1789	0.224
1790	1.115
1791	1.026
1792	1.18
1793	1.168
1794	1.097
1795	0.949
1796	0.938
1797	0.887
1798	0.9
1799	1.19
1800	0.984
1801	0.568
1802	1.129
1803	1.289
1804	1.025
1805	0.835
1806	0.898
1807	1.061
1808	0.805
1809	0.795
1810	1.15
1811	0.907
1812	1.051
1813	1.064
1814	1.158
1815	1.039
1816	1.277
1817	1.198
1818	1.041
1819	1.369
1820	1.229
1821	1.113
1822	1.089
1823	0.85
1824	0.58
1825	0.855
1826	0.98
1827	1.002
1828	1.2
1829	1.191
1830	1.128
1831	1.249
1832	0.924
1833	1.394
1834	1.086
1835	1.376
1836	1.445
1837	1.572
1838	1.516
1839	1.517
1840	1.292
1841	1.044
1842	0.534
1843	0.69
1844	0.783
1845	0.631
1846	0.702
1847	0.515
1848	0.705
1849	0.771
1850	0.802
1851	0.169
1852	0.881
1853	0.979
1854	0.995
1855	0.589
1856	0.45
1857	0.83
1858	1.243
1859	0.903
1860	1.152
1861	0.342
1862	0.808
1863	0.16
1864	0.934
1865	0.537
1866	1.077
1867	0.863
1868	0.972
1869	1.207
1870	1.085
1871	0.716
1872	0.914
1873	0.899
1874	0.783
1875	0.542
1876	1.232
1877	0.862
1878	1.031
1879	1.077
1880	0.204
1881	0.614
1882	1.048
1883	1.064
1884	1.095
1885	1.19
1886	1.083
1887	1.215
1888	1.027
1889	1.396
1890	1.112
1891	1.426
1892	1.427
1893	0.876
1894	1.422
1895	1.31
1896	0.836
1897	1.185
1898	1.19
1899	0.59
1900	0.965
1901	1.005
1902	0.889
1903	1.177
1904	1.151
1905	0.923
1906	1.408
1907	1.545
1908	0.999
1909	1.38
1910	1.153
1911	0.948
1912	1.08
1913	0.914
1914	1.082
1915	0.958
1916	1.004
1917	0.867
1918	0.931
1919	0.836
1920	0.712
1921	0.966
1922	0.819
1923	1.016
1924	0.934
1925	0.8
1926	1.298
1927	1.026
1928	1.236
1929	0.887
1930	1.136
1931	1.114
1932	0.779
1933	0.982
1934	0.335
1935	1.074
1936	0.747
1937	1.095
1938	1.04
1939	0.563
1940	1.186
1941	1.093
1942	1.315
1943	1.427
1944	1.345
1945	1.276
1946	0.748
1947	1.507
1948	1.077
1949	1.291
1950	0.472
1951	0.902
1952	0.654
1953	0.831
1954	0.464
1955	0.723
1956	0.46
1957	0.884
1958	0.959
1959	0.789
1960	0.942
1961	1.189
1962	0.981
1963	0.217
1964	0.707
1965	0.936
1966	0.53
1967	1.13
1968	0.741
1969	1.277
1970	1.076
1971	1.04
1972	1.043
1973	1.063
1974	1.136
1975	1.054
1976	0.676
1977	0.983
1978	1.033
1979	1.044
1980	0.727
1981	1.258
1982	1.2
1983	1.408