# northamerica_usa_wa037 - Bear Creek - 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/2878
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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_wa037 - Bear Creek - 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: Bear Creek
#	Location:
#	Country: United States
#	Northernmost_Latitude: 48.28
#	Southernmost_Latitude: 48.28
#	Easternmost_Longitude: -120.23
#	Westernmost_Longitude: -120.23
#	Elevation: 1085 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa037B
#	Earliest_Year: 1718
#	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":"2.76882625676","T2":"13.2430886179","M1":"0.0235478661278","M2":"0.565557939108"}}
#--------------------
# 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
1718	0.946
1719	0.647
1720	0.623
1721	0.621
1722	0.75
1723	0.874
1724	0.659
1725	0.822
1726	0.924
1727	1.182
1728	0.887
1729	0.97
1730	0.924
1731	0.897
1732	1.017
1733	0.997
1734	0.941
1735	1.025
1736	0.884
1737	0.842
1738	1.157
1739	0.698
1740	0.813
1741	0.764
1742	1.152
1743	1.315
1744	1.196
1745	1.359
1746	1.126
1747	1.339
1748	1.21
1749	1.232
1750	1.628
1751	1.227
1752	1.385
1753	1.039
1754	1.315
1755	1.587
1756	0.93
1757	0.947
1758	1.152
1759	0.756
1760	0.971
1761	1.444
1762	1.216
1763	1.065
1764	0.85
1765	1.116
1766	1.033
1767	0.87
1768	0.928
1769	1.008
1770	0.9
1771	1.054
1772	0.98
1773	1.181
1774	1.276
1775	1.14
1776	0.9
1777	1.013
1778	1.043
1779	0.834
1780	0.983
1781	1.015
1782	0.76
1783	0.102
1784	0.569
1785	0.873
1786	0.745
1787	0.616
1788	0.844
1789	1.086
1790	0.813
1791	1.187
1792	1.059
1793	1.042
1794	0.73
1795	0.705
1796	0.858
1797	0.757
1798	0.692
1799	0.715
1800	0.874
1801	1.137
1802	1.107
1803	0.897
1804	0.995
1805	0.965
1806	0.978
1807	0.855
1808	0.981
1809	1.127
1810	1.148
1811	1.038
1812	1.203
1813	1.267
1814	1.318
1815	1.172
1816	0.861
1817	0.817
1818	1.015
1819	1.154
1820	0.993
1821	0.824
1822	0.849
1823	0.521
1824	0.643
1825	0.862
1826	0.905
1827	0.764
1828	0.744
1829	0.925
1830	0.985
1831	0.876
1832	1.151
1833	1.233
1834	0.921
1835	1.115
1836	1.129
1837	1.211
1838	0.999
1839	0.726
1840	0.802
1841	0.87
1842	0.667
1843	0.653
1844	0.609
1845	1.211
1846	1.224
1847	0.787
1848	0.693
1849	0.689
1850	0.749
1851	0.613
1852	0.635
1853	0.991
1854	0.855
1855	0.889
1856	0.942
1857	0.858
1858	0.947
1859	1.086
1860	0.934
1861	1.294
1862	1.033
1863	0.95
1864	0.953
1865	0.897
1866	1.143
1867	1.094
1868	0.984
1869	0.776
1870	0.814
1871	0.626
1872	0.816
1873	0.8
1874	0.62
1875	0.678
1876	0.924
1877	0.936
1878	1.172
1879	1.148
1880	1.111
1881	1.346
1882	1.203
1883	1.1
1884	1.334
1885	1.621
1886	1.177
1887	1.029
1888	1.571
1889	0.629
1890	0.746
1891	0.904
1892	0.954
1893	1.098
1894	1.293
1895	1.297
1896	1.286
1897	1.329
1898	1.218
1899	0.933
1900	1.43
1901	1.322
1902	1.142
1903	1.445
1904	1.459
1905	1.375
1906	1.42
1907	1.276
1908	1.329
1909	1.061
1910	0.982
1911	1.069
1912	0.98
1913	1.169
1914	1.322
1915	1.387
1916	1.219
1917	0.885
1918	0.764
1919	0.976
1920	0.501
1921	1.127
1922	0.652
1923	0.704
1924	0.559
1925	0.69
1926	0.41
1927	0.725
1928	0.464
1929	0.273
1930	0.282
1931	0.15
1932	0.295
1933	0.353
1934	0.461
1935	0.583
1936	0.608
1937	0.673
1938	1.131
1939	0.71
1940	0.945
1941	1.191
1942	1.508
1943	1.046
1944	1.048
1945	0.887
1946	1.177
1947	1.011
1948	0.936
1949	1.31
1950	1.231
1951	1.225
1952	1.399
1953	1.252
1954	1.403
1955	1.441
1956	1.232
1957	1.222
1958	1.076
1959	1.394
1960	1.301
1961	1.164
1962	0.836
1963	1.153
1964	0.865
1965	0.763
1966	0.965
1967	1.022
1968	1.032
1969	1.01
1970	0.874
1971	1.154
1972	1.279
1973	0.815
1974	0.792
1975	0.634