# northamerica_usa_ct001 - Bigelow Pond - 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.
#
#
# Online_Resource:
#
# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611
#
# Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/2961
#
# Description/Documentation lines begin with #
# Data lines have no #
#
# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_usa_ct001 - Bigelow Pond - 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.
#------------------
# 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
#------------------
# Site_Information
#	Site_Name: Bigelow Pond
#	Location:
#	Country: United States
#	Northernmost_Latitude: 41.95
#	Southernmost_Latitude: 41.95
#	Easternmost_Longitude: -73.22
#	Westernmost_Longitude: -73.22
#	Elevation: 250 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_ct001B
#	Earliest_Year: 1696
#	Most_Recent_Year: 1985
#	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":"4.72316592538","T2":"14.3060465225","M1":"0.0225005171211","M2":"0.523998596642"}}
#--------------------
# Species
#	Species_Name: eastern hemlock
#	Species_Code: TSCA
#--------------------
# Chronology:
#
#
#
#--------------------
# 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
1696	1.014
1697	1.179
1698	0.913
1699	1.074
1700	1.314
1701	1.298
1702	1.276
1703	1.476
1704	0.841
1705	0.835
1706	1.13
1707	1.342
1708	1.116
1709	1.144
1710	1.018
1711	0.962
1712	0.859
1713	0.66
1714	0.626
1715	0.435
1716	0.513
1717	0.795
1718	1.067
1719	1.135
1720	1.008
1721	1.165
1722	1.024
1723	0.639
1724	0.549
1725	0.711
1726	0.585
1727	0.726
1728	0.566
1729	0.414
1730	0.639
1731	0.662
1732	0.584
1733	0.41
1734	0.562
1735	0.498
1736	0.396
1737	0.407
1738	0.652
1739	0.608
1740	0.711
1741	0.323
1742	0.572
1743	0.601
1744	0.767
1745	0.721
1746	0.668
1747	0.65
1748	0.521
1749	0.56
1750	0.713
1751	0.801
1752	0.796
1753	0.605
1754	0.514
1755	0.399
1756	0.583
1757	0.502
1758	0.574
1759	0.419
1760	0.614
1761	0.63
1762	0.756
1763	0.778
1764	0.815
1765	0.708
1766	0.749
1767	0.522
1768	0.551
1769	1.001
1770	0.727
1771	0.811
1772	0.727
1773	0.774
1774	0.989
1775	0.918
1776	0.877
1777	1.071
1778	0.858
1779	0.74
1780	0.464
1781	0.446
1782	0.692
1783	0.675
1784	0.474
1785	0.453
1786	0.585
1787	0.62
1788	0.741
1789	0.955
1790	0.757
1791	0.778
1792	0.625
1793	0.865
1794	0.589
1795	0.685
1796	0.592
1797	0.599
1798	0.516
1799	0.603
1800	0.847
1801	0.994
1802	1.158
1803	1.275
1804	1.069
1805	1.171
1806	0.953
1807	1.223
1808	1.493
1809	1.333
1810	1.305
1811	1.293
1812	1.322
1813	1.177
1814	1.272
1815	1.445
1816	1.171
1817	1.317
1818	1.146
1819	0.984
1820	1.007
1821	1.264
1822	1.447
1823	1.315
1824	1.194
1825	1.114
1826	0.885
1827	1.066
1828	1.467
1829	1.055
1830	1.064
1831	0.823
1832	0.88
1833	1.117
1834	1.401
1835	0.994
1836	0.876
1837	0.86
1838	1.113
1839	0.747
1840	0.979
1841	0.924
1842	1.215
1843	1.054
1844	1.009
1845	1.149
1846	1.18
1847	1.277
1848	1.323
1849	1.252
1850	1.121
1851	1.236
1852	1.147
1853	1.229
1854	1.238
1855	1.132
1856	0.936
1857	0.802
1858	1.378
1859	1.635
1860	1.909
1861	1.912
1862	1.365
1863	1.893
1864	1.488
1865	1.486
1866	2.087
1867	2.141
1868	1.914
1869	0.951
1870	0.974
1871	1.321
1872	1.18
1873	1.102
1874	1.923
1875	1.699
1876	1.375
1877	1.287
1878	1.386
1879	1.228
1880	1.615
1881	1.199
1882	1.662
1883	1.533
1884	1.83
1885	1.109
1886	1.107
1887	1.072
1888	1.03
1889	1.637
1890	1.693
1891	1.433
1892	1.66
1893	1.387
1894	1.53
1895	0.632
1896	0.865
1897	1.186
1898	1.284
1899	0.51
1900	0.608
1901	0.64
1902	1.015
1903	1.274
1904	1.27
1905	0.964
1906	1.032
1907	1.087
1908	0.957
1909	0.912
1910	0.91
1911	0.784
1912	0.816
1913	0.901
1914	0.74
1915	0.862
1916	1.061
1917	0.897
1918	0.58
1919	0.681
1920	0.49
1921	0.846
1922	0.743
1923	0.772
1924	0.579
1925	0.884
1926	0.644
1927	0.971
1928	1.135
1929	0.757
1930	0.856
1931	0.867
1932	0.759
1933	0.731
1934	0.524
1935	0.865
1936	0.885
1937	0.882
1938	0.888
1939	0.8
1940	0.602
1941	0.68
1942	0.59
1943	0.69
1944	0.396
1945	0.482
1946	0.765
1947	0.788
1948	0.669
1949	0.722
1950	0.569
1951	0.961
1952	0.745
1953	0.768
1954	0.844
1955	0.817
1956	0.534
1957	0.682
1958	0.643
1959	0.726
1960	0.373
1961	0.717
1962	0.506
1963	0.649
1964	0.551
1965	0.671
1966	0.608
1967	0.932
1968	0.811
1969	0.529
1970	0.68
1971	0.688
1972	0.585
1973	0.997
1974	0.762
1975	0.899
1976	0.836
1977	0.891
1978	0.782
1979	0.804
1980	0.871
1981	0.825
1982	0.686
1983	0.837
1984	0.517
1985	0.787