# northamerica_usa_or001 - Long Prairie Spring - 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/2902
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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_or001 - Long Prairie Spring - 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: Long Prairie Spring
#	Location:
#	Country: United States
#	Northernmost_Latitude: 45.15
#	Southernmost_Latitude: 45.15
#	Easternmost_Longitude: -120.12
#	Westernmost_Longitude: -120.12
#	Elevation: 1224 m
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# Data_Collection
#	Collection_Name: northamerica_usa_or001B
#	Earliest_Year: 1719
#	Most_Recent_Year: 1975
#	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":"4.4819257713","T2":"16.1954492265","M1":"0.0227920537791","M2":"0.454309589014"}}
#--------------------
# 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
1719	1.141
1720	1.136
1721	0.602
1722	0.973
1723	1.216
1724	0.924
1725	1.017
1726	1.024
1727	1.277
1728	0.667
1729	0.946
1730	0.95
1731	1.119
1732	1.469
1733	1.17
1734	1.183
1735	1.228
1736	0.742
1737	1.019
1738	1.061
1739	1.2
1740	0.793
1741	0.615
1742	0.823
1743	0.915
1744	0.74
1745	0.923
1746	1.119
1747	1.118
1748	0.798
1749	0.944
1750	1.295
1751	1.018
1752	0.805
1753	0.619
1754	0.546
1755	0.82
1756	0.53
1757	0.626
1758	0.863
1759	0.715
1760	0.853
1761	1.31
1762	1.168
1763	1.294
1764	0.794
1765	1.111
1766	1.251
1767	1.02
1768	0.847
1769	0.881
1770	1.24
1771	0.951
1772	0.859
1773	1.245
1774	1.314
1775	1.453
1776	1.071
1777	1.202
1778	1.084
1779	1.128
1780	1.191
1781	1.062
1782	1.073
1783	0.745
1784	1.012
1785	1.196
1786	1.0
1787	0.642
1788	0.823
1789	1.157
1790	0.953
1791	1.451
1792	0.948
1793	1.174
1794	1.132
1795	0.98
1796	0.946
1797	0.441
1798	0.719
1799	1.079
1800	0.803
1801	1.118
1802	1.154
1803	0.887
1804	0.803
1805	0.835
1806	0.622
1807	0.458
1808	0.56
1809	0.71
1810	0.654
1811	0.802
1812	1.069
1813	0.994
1814	1.326
1815	1.171
1816	1.177
1817	1.107
1818	1.245
1819	1.228
1820	1.02
1821	0.947
1822	1.087
1823	0.824
1824	1.193
1825	1.32
1826	1.143
1827	0.889
1828	1.104
1829	1.015
1830	0.874
1831	0.761
1832	1.065
1833	1.098
1834	0.994
1835	0.747
1836	0.826
1837	0.805
1838	0.963
1839	0.725
1840	0.581
1841	0.693
1842	0.699
1843	0.615
1844	0.655
1845	0.925
1846	0.768
1847	0.564
1848	0.64
1849	0.537
1850	0.631
1851	0.813
1852	0.914
1853	0.883
1854	0.979
1855	1.371
1856	0.967
1857	0.952
1858	0.99
1859	0.769
1860	0.954
1861	1.148
1862	1.115
1863	1.024
1864	0.949
1865	0.911
1866	0.942
1867	0.93
1868	1.116
1869	0.996
1870	0.807
1871	0.746
1872	0.712
1873	0.81
1874	0.924
1875	0.994
1876	1.015
1877	1.42
1878	1.178
1879	1.135
1880	0.915
1881	1.357
1882	1.165
1883	0.874
1884	0.963
1885	1.491
1886	0.981
1887	0.99
1888	1.038
1889	0.838
1890	0.699
1891	1.179
1892	1.235
1893	1.081
1894	1.548
1895	1.361
1896	1.112
1897	1.55
1898	1.406
1899	0.874
1900	1.58
1901	1.506
1902	1.136
1903	1.401
1904	1.981
1905	1.359
1906	1.49
1907	1.748
1908	1.835
1909	1.283
1910	1.231
1911	1.125
1912	1.296
1913	1.737
1914	1.33
1915	1.315
1916	1.317
1917	1.016
1918	0.769
1919	0.912
1920	0.728
1921	1.216
1922	0.865
1923	0.885
1924	0.747
1925	0.674
1926	0.859
1927	0.867
1928	1.009
1929	0.709
1930	0.432
1931	0.499
1932	0.579
1933	0.428
1934	0.581
1935	0.513
1936	0.454
1937	0.513
1938	0.689
1939	0.634
1940	0.696
1941	1.196
1942	1.58
1943	0.975
1944	0.732
1945	0.729
1946	0.798
1947	0.957
1948	0.915
1949	0.821
1950	0.813
1951	0.82
1952	0.721
1953	0.74
1954	0.946
1955	1.003
1956	1.124
1957	1.01
1958	1.106
1959	0.603
1960	0.773
1961	0.878
1962	0.768
1963	1.021
1964	1.009
1965	1.15
1966	1.398
1967	1.141
1968	0.918
1969	1.026
1970	0.969
1971	1.053
1972	0.989
1973	0.815
1974	0.751
1975	0.381