# northamerica_usa_ca559 - Squaw Valley   Lake Tahoe - 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/2856
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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
#--------------------
# Title
#	Study_Name: northamerica_usa_ca559 - Squaw Valley   Lake Tahoe - 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.
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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: Squaw Valley   Lake Tahoe
#	Location:
#	Country: United States
#	Northernmost_Latitude: 39.1
#	Southernmost_Latitude: 39.1
#	Easternmost_Longitude: -120.27
#	Westernmost_Longitude: -120.27
#	Elevation: 2280 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ca559B
#	Earliest_Year: 1764
#	Most_Recent_Year: 1983
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.1454015846","T2":"14.8991936689","M1":"0.0222878149463","M2":"0.428931244166"}}
#--------------------
# Species
#	Species_Name: California red fir
#	Species_Code: ABMA
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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
1764	1.064
1765	1.028
1766	0.832
1767	0.972
1768	1.129
1769	0.912
1770	0.98
1771	0.888
1772	1.0
1773	1.104
1774	1.047
1775	0.978
1776	0.924
1777	0.867
1778	0.939
1779	1.003
1780	1.092
1781	0.986
1782	0.968
1783	0.895
1784	0.997
1785	1.014
1786	1.102
1787	0.885
1788	0.967
1789	1.078
1790	0.866
1791	1.303
1792	1.147
1793	1.137
1794	1.193
1795	0.881
1796	0.822
1797	0.889
1798	1.125
1799	0.871
1800	1.076
1801	0.864
1802	1.012
1803	1.159
1804	1.137
1805	1.111
1806	1.12
1807	1.112
1808	1.172
1809	1.028
1810	0.752
1811	0.634
1812	1.045
1813	1.102
1814	1.177
1815	1.048
1816	1.071
1817	1.253
1818	1.205
1819	0.914
1820	1.122
1821	1.1
1822	0.903
1823	0.812
1824	0.752
1825	0.749
1826	1.075
1827	1.014
1828	0.959
1829	0.943
1830	0.833
1831	0.78
1832	0.993
1833	1.054
1834	1.042
1835	1.016
1836	0.82
1837	1.105
1838	1.058
1839	1.223
1840	1.024
1841	1.086
1842	0.824
1843	1.052
1844	0.817
1845	0.981
1846	0.936
1847	0.777
1848	1.106
1849	0.949
1850	0.875
1851	1.062
1852	1.046
1853	0.928
1854	1.092
1855	1.025
1856	0.767
1857	0.916
1858	0.999
1859	0.839
1860	0.897
1861	1.058
1862	0.756
1863	1.346
1864	1.102
1865	0.979
1866	1.025
1867	0.842
1868	0.973
1869	1.247
1870	0.985
1871	0.782
1872	0.699
1873	1.03
1874	0.732
1875	0.935
1876	0.971
1877	1.187
1878	1.024
1879	1.175
1880	0.811
1881	1.073
1882	1.063
1883	0.943
1884	0.872
1885	1.072
1886	1.015
1887	0.858
1888	0.802
1889	0.594
1890	0.491
1891	0.854
1892	0.86
1893	0.905
1894	0.931
1895	0.995
1896	0.91
1897	1.048
1898	0.909
1899	0.755
1900	0.981
1901	1.171
1902	0.993
1903	0.968
1904	1.351
1905	1.165
1906	0.94
1907	1.1
1908	1.422
1909	1.043
1910	0.977
1911	0.873
1912	0.994
1913	1.005
1914	1.067
1915	1.19
1916	1.069
1917	1.09
1918	0.98
1919	1.033
1920	0.913
1921	0.929
1922	0.927
1923	0.91
1924	1.005
1925	0.929
1926	1.053
1927	0.9
1928	0.95
1929	0.853
1930	0.849
1931	0.918
1932	0.77
1933	0.861
1934	0.938
1935	1.039
1936	1.162
1937	1.139
1938	1.182
1939	1.326
1940	1.097
1941	1.041
1942	1.398
1943	1.565
1944	1.373
1945	1.297
1946	1.265
1947	1.444
1948	1.408
1949	1.068
1950	1.182
1951	1.096
1952	0.869
1953	1.119
1954	1.317
1955	1.06
1956	0.803
1957	1.271
1958	1.307
1959	1.35
1960	1.037
1961	1.033
1962	1.162
1963	1.167
1964	0.847
1965	0.601
1966	0.739
1967	0.865
1968	1.096
1969	1.119
1970	1.319
1971	0.889
1972	0.442
1973	0.58
1974	0.594
1975	0.477
1976	0.68
1977	0.713
1978	0.854
1979	1.058
1980	0.938
1981	0.914
1982	0.796
1983	1.027