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S5–P2
㻶㻘㻐㻳㻕Global methane simulation for the period 1910-2010 using
atmospheric general circulation model based chemistry transport
model
Arindam Ghosh1,2, Prabir K. Patra2, Kentaro Ishijima2, Shinji Morimoto1, Kenji
Kawamura1,3, Satoshi Sugawara4, Akihiko Ito5, Shuji Aoki6, and Takakiyo
Nakazawa6,2
1.
2.
3.
4.
5.
6.

National Institute for Polar Research, Tokyo, Japan
Research Institute for Global Change/JAMSTEC, Yokohama, Japan
Institute of Beogeosciences/JAMSTEC, Yokosuka, Japan
Miyagi Univ. of Education, Sendai, Japan
National Institute for Environmental Studies, Tsukuba, Japan
Center for Atmospheric and Oceanic Studies, Tohoku University, Sendai,JapanE-mail address of corresponding author: arindam@jamstec.go.jp

Methane (CH4) is produced both naturally and anthropogenically on the Earth’s
surface, and thought to be second only to carbon dioxide (CO2) as an agent ofpresent/future global warming. Methane is also chemically active, contributing toformation of tropospheric ozone and stratospheric water vapor, which further
increases its importance to the Earth’s radiative balance. Atmospheric CH4
concentration has increased from 900 ppb in 1900 to ~1800 ppb in 2000s [1]. During
the same period, the anthropogenic CH4 emission has increased from 92 Tg/yr toabout 310 Tg/yr. Mass balance calculation suggest that the increase in atmosphericconcentration is caused entirely due to increase in anthropogenic emissions [2].
Model simulations of atmospheric CH4 at monthly time scale with a horizontal
resolution of T42 spectral truncation (~2.8x2.8°) and 67 sigma-pressure verticallayers (surface - ~90 km), for ten different emission scenarios based on combinationsof anthropogenic (fossil fuel, biofuel, industrial process, livestock, waste handling andfire) and natural (wetland and rice) emission types, are being conducted using the
CCSR/NIES/FRCGC Atmospheric General Circulation Model (AGCM) based
Chemistry Transport Model (ACTM) for the period of 1900-2010. The model
simulations will be compared with CH4 concentrations as measured from the air
bubbles trapped in the polar ice columns, and direct measurements since the 1970s
at multiple sites around the globe.
Results on the contribution of different CH4 emission types to latitudinal and interannual/decadal variation of CH4 concentration over the past century will be
discussed.
References:[1] Etheridge, D.M., L.P. Steele, R.J. Francey, and R.L. Langenfelds. 1998.
Atmospheric methane between 1000 A.D. and present: evidence of anthropogenic
emissions and climatic variability. Journal of Geophysical Research, 103, 1597915996.
[2]
EDGAREmission
Databasefor
Global(http://edgar.jrc.ec.europa.eu/archived_datasets.php)
㻔㻕㻜AtmosphericResearch㻶㻘㻐㻳㻖
S5–P3

 OCEANIC AND TERRESTRIAL BIOSPHERIC CO2UPTAKE ESTIMATED FROM ATMOSPHERIC POTENTIALOXYGEN OBSERVED AT NY-ÅLESUND, SVALBARD AND
SYOWA, ANTARCTICA
Shigeyuki Ishidoya1, Shinji Morimoto2, Shuji Aoki3, Shoichi Taguchi1, Daisuke
Goto3, Shohei Murayama1 and Takakiyo Nakazawa3
1

National Institute of Advanced Industrial Science and Technology (AIST),
Tsukuba 305-8569, Japan,23National Institute of Polar Research, Tokyo 190-8518, Japan,

Center for Atmospheric and Oceanic Studies, Tohoku University, Sendai
980-8578, Japan.
E-mail: s-ishidoya@aist.go.jp

Simultaneous measurements of the atmospheric O2/N2 ratio and CO2
concentration were made at Ny-Ålesund, Svalbard and Syowa, Antarctica for theperiod 2001-2009. Based on these measurements, the observed atmosphericpotential oxygen (APO) values were calculated. The APO variations produced bychanges in the oceanic heat content were estimated using an atmospherictransport model and heat-driven air-sea O2 (N2) fluxes, and then subtracted fromobserved interannual variations of APO. The oceanic CO2 uptake derived from theresulting “corrected” secular trend of APO showed interannual variability of lessthan ±0.6 GtC yr-1, significantly smaller than that derived from the “uncorrected”
trend of APO (±0.9 GtC yr-1). The average CO2 uptake during the period
2001-2009 was estimated to be 2.9±0.7 and 0.8±0.8 GtC yr-1 for the ocean andterrestrial biosphere, respectively. By excluding the influence of El Niño around2002-2003, the terrestrial biospheric CO2 uptake for the period 2004-2009
increased to 1.5±0.8 GtC yr-1, while the oceanic uptake decreased slightly to
2.8±0.7 GtC yr-1.

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TIME SERIES OF TROPOSPHERIC N2O ISOTOPOMERRATIOS OVER WESTERN SIBERIA
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Department of Environmental Science and Technology, 2Department of1

Environmental Chemistry and Engineering, Tokyo Institute of Technology, 4259
Nagatsuta, Midori-ku, Yokohama 226-8502, Japan
3

Research Institute for Global Change, Japan Agency for Marine-Earth Scienceand Technology, 3173-25 Showamachi, Kanazawa-ku, Yokohama 236-0001,
Japan
4

National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, 305-8506,

Japan
toyoda.s.aa@m.titech.ac.jp
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1
National Institute for Environmental Studies, Tsukuba 308-8506, Japan
2
Tokyo University of Agriculture and Technology, 184-8588, Japan
E-mail: tohjima@nies.go.jp
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S5–P7

HIGH PRECISION CONTINUOUS MEASUREMENT SYSTEMFOR THE ATMOSPHERIC O2/N2 RATIO AT NY-ÅLESUND,SVALBARD
Daisuke Goto1, Shinji Morimoto2, Shigeyuki Ishidoya1, Shuji Aoki1 and Takakiyo
Nakazawa1
1: Center for Atmospheric and Oceanic Studies, Tohoku University, Sendai

980-8578, Japan2: National Institute of Polar Research, Tokyo190-8518, Japan

Contact address: d_goto@caos-a.geophys.tohoku.ac.jp
To elucidate temporal variations of atmospheric O2 at Ny-Ålesund (79˚N,
12˚E), Svalbard in detail, as well as to contribute to a better understanding of the
global carbon cycle, a high precision continuous measurement system for theatmospheric O2/N2 ratio was developed using a fuel cell oxygen analyzer. To
obtain highly precise values of the atmospheric O2/N2 ratio, pressure fluctuationsof the sample and standard air in the fuel cells were reduced to an order of 10−3
Pa, with temperatures stabilized to 32.0±0.1ºC. A non-dispersive infrared analyzer
was also installed into the system to allow simultaneous measurements of theatmospheric CO2 concentration. Considering remoteness of the observation site,
three special attentions were further paid when the measurement system wasconstructed; (1) the start-up and shutdown of the system can be controlled inJapan using the Internet, (2) all the output data from the system are recorded on ahard disk and also collected in Japan through the Internet, and (3) two water traps
were equipped in parallel on the air sample line to make it possible to operate thesystem over a long time without manually replacing the trap. The two traps arealternately switched to cool at −80ºC and heat at 50ºC in order to remove water
vapor contained in the sample air and the trap, respectively. By repeatedly
analyzing the same sample air, the analytical precision of the measurement
system was estimated to be ±1.4 per meg (0.3 ppm), which is sufficient for clearly
detecting very small spatiotemporal variations of the atmospheric O2/N2 ratio. We
also tested the system by continuously measuring the O2/N2 ratio in the boundary
layer atmosphere at Aobayama (38˚N, 141˚E), Sendai, Japan, and it was
confirmed that the system is capable of clearly detecting very small but persistentseasonal and diurnal cycles, along with short-term variations on time scales ofseveral hours to several days, caused by terrestrial biospheric and humanactivities. Systematic and continuous observation of the atmospheric O2/N2 ratiousing the developed system is planed to start at Ny-Ålesund in December 2012.

㻔㻖㻗㻶㻘㻐㻳㻛S5–P8

APPLICATION OF RADON-222 AS A TRACER FOR
CHARACTERIZING FETCH REGIONS AND EVALUATING A
GLOBAL 3D MODEL
Chunmao Zhu1, Hisayuki Yoshikawa-Inoue1, Hidekadzu Matsueda2, Yosuke Sawa2,
Yosuke Niwa2, Akira Wada3, Hiroshi Tanimoto4
1

Graduate School of Environmental Science, Hokkaido University, North 10 West 5,
North District, Sapporo 060-0810, Japan
2
Geochemical Research Division, Meteorological Research Institute, Nagamine 1-1,
Tsukuba 305-0052, Japan
3
Meteorological College, Asahi-cho, Kashiwa 277-0852, Japan
4
National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 3058506, Japan
Corresponding author: Chunmao Zhu; E-mail: chmzhu@ees.hokudai.ac.jp
In order to estimate the regional/continental sources and sinks for atmosphericCO2, atmospheric Radon-222 has been used at Rishiri Island (45°07’N, 141°12’E)
as a tracer being monitored since December 2008. This work analyzed the first two
years atmospheric Radon-222 data to evaluate the seasonal transport pattern. In
summer, clear diurnal variation was observed with maximum Radon-222
concentration before the dawn, while the minimum appeared in the afternoon. Thiswas caused by the local radon-222 source. However the magnitude of local source
was quite weak. Seasonal Radon-222 variation was characterized by highconcentrations from November to February and low concentrations from May to
July, caused by the alternation of continental and maritime fetch regions. Seasonalhigh and low Radon-222 events were examined by using the back trajectory cluster
analyses to clarify the fetch regions (Fig.
1). The results indicated that the
predominant continental fetch region was
southeastern Siberia and northeastern
China. Radon-222 emitted from China andSouth Korea, whose economies are
growing rapidly, did not significantly affect
the Rishiri site. This implies that current
observation of CO2 at Rishiri Island ismore directly influenced by the carbon
sink region vegetated by boreal forest.
The major maritime fetch region was the
Sea of Okhotsk and the Bering Sea. A
global three-dimensional model (NICAMTM) accurately simulated Radon-222
concentrations on Rishiri Island and in theseasonal fetch regions. Other than toevaluate the sources of atmosphericgreenhouse gases being monitored at
Rishiri Island, the time series of RadonFig. 1. Fetch regions for high and low radon-222
222 data will also allow us to validate
events at RIO as indicated by 120-h back trajectorymodel simulations used to examine
clusters. The values near each trajectory show thetrans-boundary air pollution.
ratio of events contributing to that cluster relative tototal events in the specified season.

㻔㻖㻘㻶㻘㻐㻳㻜
S5–P9

RECONSTRUCTION OF PAST VARIATIONS OF THE
CARBON AND HYDROGEN ISOTOPIC RATIOS IN
ATMOSPHERICMETHANEFROMITSVERTICAL
DISTRIBUTION OBSERVED IN NGRIP FIRN
Satoshi Sugawara1, Taku Umezawa2, Kenji Kawamura3, Shinji Morimoto3,
Shuji Aoki4 and Takakiyo Nakazawa4
1

Institute of Earth Science, Miyagi University of Education, Sendai, Japan
Max Planck Institute for Chemistry, Mainz, Germany3
National Institute of Polar Research, Tokyo, Japan
4
Center for Atmospheric and Oceanic Studies, Tohoku University, Sendai, Japan(sugawara@staff.miyakyo-u.ac.jp)
2

Temporal variations of δ13C and δD of atmospheric CH4 in the past 50 years werereconstructed from the isotopic ratios of CH4 observed in firn at North GRIP. The
one-dimensional diffusion model was used to simulate the diffusion process andthe gravitational separation of CH4 molecule in the firn. The effective diffusivity
was determined so that the difference between the modeled and observed CO2
concentration profiles was minimized. An approximate history of the atmosphericCH4 concentration was constructed for NGRIP by combining the data from thedirect atmospheric measurements at Point Barrow, Alert, and Ny-Ålesund withthose from ice cores at Greenland. In order to reconstruct the past δ13C and δDof atmospheric CH4 from their values in the firn, the effective age of CH4 at eachsampling depth was determined by using an approximate history of theatmospheric CH4 concentration. Effective age at each sampling depth was
determined so that the model-calculated concentration at that depth agreed with avalue in the concentration history. To correct for the diffusion effect on δ13C of CH4
in the firn, the diffusion model was run without the gravitational effect, using
concentration histories for three kinds of CH4 molecules, 12CH4 with D16, 13CH4
with D17, and 13CH4 with D16. Here, D16 and D17 represent the effective diffusivities
of CH4 molecules with masses 16 and 17, respectively. The diffusion correction
was determined as a difference between the isotopic value of the heavier
molecule actually predicted in the firn (δ13C(D17)) and the value which theoretically
excluded the effect of diffusive separation (δ13C(D16)). Correction for the diffusion
effect on δD was the same as that of δ13C, but used three molecules of CH4 with
D16, CH3D with D17 and CH3D with D16. The values of the atmospheric δ13C, thus
estimated, were in good agreement with those from direct atmosphericmeasurements at Ny-Ålesund. The statistical uncertainty of the reconstruction
procedure was examined by repeating model calculation with 100 different data
sets provided by adding normal pseudo random numbers to the observed values
in firn. We will also discuss an application of the diffusion correction to the isotopic
values of CH4 observed by ice core analyses.

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S5–P12
Arctic Data archive System (ADS)
Hironori Yabuki1,2,

Haruko Kawamoro1

1 Arctic Environment Research Center (AERC), National Institute of Polar
Research (NIPR),Tachikawa-shi, Tokyo, 190-8518 JAPAN2 Research Institute for Global Change(RIGC), Japan Agency for Marine-Earth
Science and Technology (JAMSTEC) Yokosuka, 237-0061, JAPANE-mail: yabuki@jamstec.go.jp
In Arctic region, various changes are being caused by global warming. In
previous studies, the decrease of Arctic sea ice extent, the increase in soil
temperature in the region of Siberia, permafrost melting, the increase in Arctic
river runoff, reduction in snow cover has been revealed. Also the impact of humanactivities and ecosystems due to these changes is concerned. The actual
condition and mechanism of environmental change in arctic has not been
elucidated. Previous studies have been carried out to separate the atmosphere,
oceans, by land. Arctic is a system consisting of atmosphere, ocean, land surface,from snow and ice, these systems including the phenomenon of different spatial
scales and time scale, respectively. In order to clarify the variability of the Arctic
environment, through interdisciplinary research, research is needed in using a
database that integrates the results of observation and research data acrossmultiple areas.
On the other hand, arctic research by Japanese researchers has been
carried out all the time from the last century. The result of their research includes
many irreplaceable data, such as observation time series, sample, and its
analysis, which each researcher got in the field. Since researcher andorganization have had those data in their keeping by their way, many data has not
managed and kept systematically.
Now, a new ‘Arctic Data archive System (ADS)’ was launched on purpose
to collect, manage and open some arctic data supported by Green Network of
Excellence (GRENE), Rapid Change of the Arctic Climate System and its Global
Influences (a tentative English title). ADS can search various keywords using
metadata which are related with a one-to-one correspondence. This schema fitssome format of typical Earth environment data, and we plan additional schema.

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S5–P15OVERVIEW OF REGIONAL AND INTERANNUAL
VARIATIONS OF SNOW AND SURFACE CONDITIONS AT
GRENE ARCTIC OBSERVATION SITES DERIVED BYSATELLITE MICROWAVE DATA1XHUDVLPXJXOL$OLPDVL+LUR\XNL(QRPRWR6KXKHL7DNDKDVKL
1

Kitami Institute of Technology, 165 Koen-cho, Kitami, Hokaido, Japan

2

National Institute of Polar Research, 10-3 Tachikawa, Tokyo, Japan

E-mail address of corresponding author: dse10841@std.kitami-it.ac.jp
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S5–P16

JAPANESE FIELD ACTIVITIES IN THE GREENLAND ICESHEET MONITORING NETWORK (GLISN)*HQWL7R\RNXQL0DVDNL.DQDR<RNR7RQR7HWVXWR+LPHQR6HLML7VXERL
1

Tohoku University, 6-6 Aza-Aoba, Aramaki, Aoba-ku, Sendai 980-8578, Japan

2

NIPR, 10-3, Midoricho, Tachikawa, Tokyo 190-8518, Japan

3

JAMSTEC, 3173-25, Showa-machi, Kanazawa-ku, Yokohama 236-0001, Japan

4

Seikei University, 3-3-1 Kichijoji-Kitamachi, Musashino, Tokyo 180-8633, Japan

toyokuni@aob.gp.tohoku.ac.jp
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S5–P17

GLACIOLOGICAL OBSERVATIONS IN SUNTAR-KHAYATARANGE, EASTERN SIBERIA, 2012
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1

Kitami Institute of Technology, 165 Koen-cho, Kitami, Hokkaido 090-8507, Japan

2

Japan Agency for Marine-Earth Science and Technology, 3173-25, Showa-machi,

Kanazawa-ku, Yokohama-city, Kanagawa 236-0001, Japan
3

Chiba University, 1-33, Yayoi-cho, Inage-ku, Chiba-shi, Chiba 263-8522, Japan

4

National Institute of Polar Research, 10-3, Midoricho, Tachikawa, Tokyo

190-8518, Japan
5

Melnikov Permafrost Institute, 677010, Yakutsk, 36, Merzlotnaya str. MPI SB

RussiaCorresponding author: Tatsuo Shirakawa, shirakaw@mail.kitami-it.ac.jp
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S5–P22SEA-ICE THICKNESS CHARACTERISTICS REVEALED BY
OBSERVATIONS IN THE CANADA BASIN
J. Ono1,2,

K. Tateyama3,

D. Hirano1,4,

A. Orlich5

1

National Institute of Polar Research, Tokyo, Japan

2

The University of Tokyo, Chiba, Japan

3

Kitami Institute of Technology, Hokkaido, Japan

4

Tokyo University of Marine Science and Technology, Tokyo, Japan

5

University of Alaska Fairbanks, Alaska, USA

E-mail: jo@1.k.u-tokyo.ac.jp
To observe ocean and sea ice conditions in the Canada Basin of the Arctic
Ocean, a scientific cruise of the Canadian Coast Guard Ship Louis S. St-Laurent
was conducted from 2 August to 8 September 2012. Using an electromagnetic
induction instrument (EM) along with Passive Microwave Radiometers (PMR),
underway measurements of sea-ice thickness were carried out on August 8 to 10(offshore of Barrow) and 27 to 29 (around 80oN). Sea-ice thicknesses measured
by the EM spatially changed with the range of 0.1-3.0 m. To reveal sea-ice
thickness distribution in more detail, probability density was examined. Although
the modal sea-ice thickness existed in 0-0.1 m, the probability density was higher
around 80oN than offshore of Barrow. Measurements of sea-ice thickness with aportable EM were also done along four transect lines at two ice stations (80.88oN,
137.41oW and 80.21oN, 129.97oW) on August 26 and 27. The mean sea-ice
thicknesses for each transect lines were 1.35, 1.34, 0.38, and 2.46 m, respectively.
From the entire data, the maximum (minimum) sea-ice thickness was 2.52 (0.26)
m. Sea-ice thicknesses obtained from the EM agree fairly well with those basedon the drill-hole measurements. The correlation coefficient between them was
0.96. In addition to the detailed discussion, results obtained from PMR andrelationship between sea ice and ocean conditions will be introduced during thepresentation of the day.

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