# asia_russ153w - Jama river - 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/4446
#
# Description/Documentation lines begin with #
# Data lines have no #
#
# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: asia_russ153w - Jama river - 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: Jama river
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 59.78
#	Southernmost_Latitude: 59.78
#	Easternmost_Longitude: 154.0
#	Westernmost_Longitude: 154.0
#	Elevation: 80 m
#--------------------
# Data_Collection
#	Collection_Name: asia_russ153wB
#	Earliest_Year: 1833
#	Most_Recent_Year: 1994
#	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":"4.64169254157","T2":"16.0523474996","M1":"0.022757372341","M2":"0.319986836676"}}
#--------------------
# Species
#	Species_Name: Siberian spruce
#	Species_Code: PCOB
#--------------------
# 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
1833	1.223
1834	0.988
1835	1.061
1836	1.109
1837	0.817
1838	0.502
1839	0.607
1840	0.718
1841	0.986
1842	1.016
1843	1.092
1844	1.251
1845	1.21
1846	1.19
1847	0.972
1848	0.826
1849	1.106
1850	0.999
1851	0.941
1852	0.692
1853	0.564
1854	0.51
1855	0.449
1856	0.39
1857	0.522
1858	0.532
1859	0.456
1860	0.429
1861	0.479
1862	0.602
1863	0.623
1864	0.919
1865	1.383
1866	0.934
1867	0.683
1868	0.991
1869	1.026
1870	1.034
1871	0.786
1872	0.938
1873	1.121
1874	1.25
1875	1.099
1876	0.998
1877	1.199
1878	1.069
1879	0.941
1880	0.911
1881	0.824
1882	0.909
1883	1.11
1884	1.229
1885	0.907
1886	0.982
1887	0.549
1888	0.33
1889	0.53
1890	0.883
1891	1.217
1892	1.143
1893	0.779
1894	0.947
1895	1.028
1896	1.106
1897	1.277
1898	1.351
1899	1.369
1900	1.221
1901	1.228
1902	1.334
1903	1.221
1904	1.08
1905	1.267
1906	1.084
1907	1.385
1908	1.157
1909	1.349
1910	1.476
1911	1.084
1912	0.928
1913	1.27
1914	0.87
1915	0.955
1916	1.02
1917	0.987
1918	0.825
1919	1.064
1920	1.088
1921	1.402
1922	1.228
1923	1.465
1924	1.36
1925	1.024
1926	0.735
1927	0.956
1928	1.175
1929	1.279
1930	0.861
1931	0.915
1932	1.018
1933	1.312
1934	1.179
1935	1.222
1936	1.132
1937	0.877
1938	0.974
1939	0.94
1940	0.995
1941	1.332
1942	1.211
1943	1.205
1944	1.21
1945	0.899
1946	1.191
1947	1.056
1948	1.419
1949	1.559
1950	1.067
1951	0.933
1952	0.889
1953	0.75
1954	1.087
1955	1.015
1956	1.281
1957	0.82
1958	0.594
1959	0.834
1960	0.947
1961	0.954
1962	1.231
1963	1.02
1964	0.954
1965	1.004
1966	1.118
1967	1.242
1968	1.159
1969	0.798
1970	0.465
1971	0.374
1972	0.557
1973	0.738
1974	0.754
1975	0.759
1976	0.834
1977	0.799
1978	0.888
1979	1.107
1980	0.901
1981	0.81
1982	0.745
1983	0.69
1984	0.417
1985	0.605
1986	1.052
1987	1.064
1988	1.032
1989	0.968
1990	1.315
1991	1.364
1992	1.028
1993	0.861
1994	0.801