# Robinson fire data from Mustei Nuur, north-central Mongolian - IMPD MNMTN001
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#               World Data Center for Paleoclimatology, Boulder
#                                   and
#                      NOAA Paleoclimatology Program
#-----------------------------------------------------------------------
# NOTE: Please cite original publication, online resource and date accessed when using this data.
# If there is no publication information, please cite Investigator, title, online resource and date accessed.
#
# Description/Documentation lines begin with #
# Data lines have no #
#
# Online_Resource: http://www.ncdc.noaa.gov/paleo/study/20514
# Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/asia/mnmtn001.txt
#
# Archive: Fire History
#
# Parameter_Keywords: 
#---------------------------------------
# Contribution_Date
#    Date: 2016-08-01
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# Title
#    Study_Name: Robinson fire data from Mustei Nuur, north-central Mongolian - IMPD MNMTN001
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# Investigators
#      Investigators: Robinson, Kevin Daniel; Umbanhowar, Charles
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# Description and Notes
#        Description: A holistic paleolimnological study of north-central Mongolian. 
#         Provided Keywords: fire, paleoclimate, climate, charcoal
#---------------------------------------
# Publication
# Authors: 
# Published_Date_or_Year: 
# Published_Title: 
# Journal_Name: 
# Volume: 
# Edition: 
# Issue: 
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# DOI: 
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# Abstract: 
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# Funding_Agency
#    Funding_Agency_Name: 
#    Grant: 
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# Site Information
# Site_Name: Mustei Nuur
# Location: Asia
# Country: Mongolia
# Northernmost_Latitude: 51.23923
# Southernmost_Latitude: 51.23923
# Easternmost_Longitude: 99.00756
# Westernmost_Longitude: 99.00756
# Elevation: 2353
#---------------------------------------
# Data_Collection
#   Collection_Name: MNMTN001-CHAR
#   First_Year: 10174.7666666255
#   Last_Year: 3.388888889
#   Time_Unit: cal yr BP
#   Core_Length: 
#   Notes: 
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# Species
#   Species_Name: 
#   Common_Name: 
#   Tree_Species_Code: 
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# Chronology_Information 
# Chronology: 
# 
# Short name	What	Units	Data type	
# ID_DATE_INFO	NaN  NaN	
# ID_SITE	Site ID	NaN  C	
# CORE_NAME	Name of core	NaN  C	
# AVG_DEPTH (cm)	Average depth of aged sample	cm	N	
# THICKNESS	Thickness of sample	cm	N	
# ID_DATE_TYPE	NaN  NaN	C	
# AGE_CALIB	Calibrated age	NaN  N	
# AGE_C14	Carbon-14 Age	NaN  N	
# ERROR	positive/negative error	NaN  N	
# LAB_NUM	Lab number	NaN  N	
# ID_MAT_DATED	NaN  NaN	NaN	
# ID_COMMENTS	NaN  NaN	C	
# AGE_BASIS	Used for age model?	NaN  C	
# 
# ID_DATE_INFO	ID_SITE	CORE_NAME	AVG_DEPTH (m)	THICKNESS	ID_DATE_TYPE	AGE_CALIB	AGE_C14	ERROR	LAB_NUM	ID_MAT_DATED	ID_COMMENTS	AGE_BASIS	
#		MUS-A-7-VIII-05	1967	1	Corrected radiocarbon date	1530	1635	50	UCI-32669	charcoal		YES
#		MUS-A-7-VIII-05	2012	1	Corrected radiocarbon date	6600	5800	40	UCI-32670	plant macrofossil		YES
#		MUS-A-7-VIII-05	2047	1	Corrected radiocarbon date	9655	8710	40	UCI-25173	plant macrofossil		YES
#---------------------------------------
# Variables
# Data variables follow that are preceded by "##" in columns one and two.
# Variables list, one per line, shortname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data)
## depth-cm-top	Depth top,,,cm ,,,,,N
## depth-cm-bottom	Depth bottom,,,cm ,,,,,N
## age-calBP	Age,,,calendar years BP,,,,,N
## char>180um	Charcoal ,wet sediment,,count,,fire history,> 180 um,,N
## vol-wetsed	Volume,wet sediment,,ml,,fire history,used for charcoal counts,,N
#------------------------
# Data
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Value: 
depth-cm-top	depth-cm-bottom	age-calBP	char>180um	vol-wetsed	
1940	1941	3.39	0	1.0	
1942	1943	236.94	1	1.0	
1945	1946	587.28	2	1.0	
1947	1948	820.83	1	1.0	
1950	1951	1171.17	1	1.0	
1952	1953	1404.72	5	1.0	
1955	1956	1755.06	1	1.0	
1957	1958	1988.61	2	1.0	
1960	1961	2338.94	0	1.0	
1962	1963	2572.50	8	1.0	
1965	1966	2922.83	0	1.0	
1967	1968	3147.78	4	1.0	
1970	1971	3446.44	3	1.0	
1972	1973	3645.56	2	1.0	
1975	1976	3944.22	7	1.0	
1977	1978	4143.33	3	1.0	
1980	1981	4442.00	3	1.0	
1982	1983	4641.11	3	1.0	
1985	1986	4939.78	4	1.0	
1987	1988	5138.89	4	1.0	
1990	1991	5437.56	2	1.0	
1992	1993	5636.67	13	1.0	
1995	1996	5935.33	3	1.0	
1997	1998	6134.44	6	1.0	
2000	2001	6433.11	2	1.0	
2002	2003	6632.22	3	1.0	
2005	2006	6930.89	18	1.0	
2007	2008	7130.00	17	1.0	
2010	2011	7428.67	16	1.0	
2012	2013	7603.69	8	1.0	
2015	2016	7757.80	12	1.0	
2017	2018	7860.54	5	1.0	
2020	2021	8014.66	5	1.0	
2022	2023	8117.40	13	1.0	
2025	2026	8271.51	5	1.0	
2027	2028	8374.26	6	1.0	
2030	2031	8528.37	11	1.0	
2032	2033	8631.11	0	1.0	
2035	2036	8785.23	1	1.0	
2037	2038	8887.97	0	1.0	
2040	2041	9042.09	1	1.0	
2042	2043	9144.83	3	1.0	
2045	2046	9298.94	3	1.0	
2047	2048	9401.77	5	1.0	
2050	2051	9556.37	13	1.0	
2052	2053	9659.43	8	1.0	
2055	2056	9814.03	4	1.0	
2057	2058	9917.10	4	1.0	
2060	2061	10071.70	0	1.0	
2062	2063	10174.77	1	1.0