NIES Supercomputer Annual Report 2007CGER-REPORT ISSN 1341-4356 CGER-I086-2008 国立環境研究所スーパーコンピュータ利用研究年報平成19 年度 NIES Supercomputer

NSSI TROPER-REGC 1341-4356

8002-680I-REGC

国立環境研究所スーパーコンピュータ利用研究年報

平成 19 年度

NIES Supercomputer Annual Report 2007

国立環境研究所地球環境研究センター編

地球環境研究センター Center for Global Environmental Research

独立行政法人国立環境研究所 National Institute for Environmental Studies, Japan

NSSI TROPER-REGC 1341-4356

8002-680I-REGC

国立環境研究所スーパーコンピュータ利用研究年報

平成 19 年度


国立環境研究所地球環境研究センター編

地球環境研究センター Center for Global Environmental Research

独立行政法人国立環境研究所 National Institute for Environmental Studies, Japan

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iii

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1.

.................................................................................................................................................... 1

2. ....................................... 13

3. ................................................... 21

4. MIROC .... 27

5. MIROC

.......................................................................................................................................... 33

6. ....................................................................................... 41

7. NICAM ............................................................................................. 49

8. ............................................................................................... 55

9. ........................... 67

10. 3 ................................................................... 75

11.

.......................................................................................................................... 83

12. ................... 89

13. CAI . ............................................... 97

iv

14. GOSAT ........................................................................ 105

15. Application of the Transport Model for Inverse Modeling Studies of the Regional and Global

Budgets of CO2 CO2

................................................................................................................................ 113

Shamil MAKSYUTOV

16. ............................................................................. 123

.................................................................... 129

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19CGER-I086-2008, CGER/NIES

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CO

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IPCC WMO

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1

2. 2.1

CPU Total 361,248hrs

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40 20 GB 10 GB /1

－ 2－－ 3－

CGER-I086-2008, CGER/NIES

MIROC SPRINTARS CHASER

GB 12 40 5.1 37 8.5 25 /1 GB 1.3 30 2 130 15 40

8000 300 3000 60 3. 3.1

1 11 2MIROC 3

SPRINTARS 4CHASER

3.2

MIROCSPRINTARS CHASER IPCC

WMO/UNEP

//

-IPCC

WMO

3.3

80 km- 1 km

CHASER

－ 4－－ 5－

11

T42 300 km SX8 21 12

1

3.4 3.4.1 11

11Shindell et al., 1999

Akiyoshi et al., 2004 11

1980 2004 2510.7 cm

32 10 Pa

50 PaLee and Smith, 2003

5

－ 4－－ 5－


2 10.7 cm

ppmv 3.4.2 MIROC

IPCC 4 IPCC, 2007 20

ab

20 a

MIROC K-1 model developers, 200420 3

3 1961 1990

－ 6－－ 7－

3.4.3 SPRINTARS

SPRINTARS Takemura et al., 2002

http://www.sprintars.net/

19904

4

3.4.4 CHASER

CHASER Sudo and Akimoto, 2007

COPoker Flat CO 2002 2003

Kasai et al., 2005 CO5 CHASER Poker Flat CO

2002 2003 CO5 CO

－ 6－－ 7－


5 Poker Flat CO 10 km

CO CO

Akiyoshi, H., Sugita, T., Kanzawa, H., Kawamoto, N. (2004) Ozone perturbations in the Arctic summer lower

stratosphere as a reflection of NOx chemistry and planetary scale wave activity. J. Geophys. Res., 109, D03304, doi:10.1029/2003JD003632.

IPCC (2007) Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt,M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 996 pp.

K-1 model developers. (2004) K-1 coupled GCM (MIROC) description. K-1 tech. rep. 1, edited by H. Hasumi and S. Emori, 34pp, Cent. for Clim. Sys. Res., Univ. of Tokyo, Tokyo.

Kasai, Y. J., Kagawa, A., Jones, N., Fujiwara, A., Seki, K., Murayama, Y., Murcray, F. (2005) Seasonal variations of CO and HCN in the troposphere measured by solar absorption spectroscopy over Poker Flat, Alaska. Geophys. Res. Let., 32, L19812, doi:10.1029/2005GL022826.

Lee, H., Smith, A.K. (2003) Simulation of the combined effects of solar cycle, quasi-biennial oscillation, and volcanic forcing on stratospheric ozone changes in recent decades. J. Geophys. Res., 108(D2), 4049, doi:10.1029/2001JD001503.

Shindell, D., Rind, D., Balachandran, N., Lean, J., Lonergan, P. (1999) Solar cycle variability, ozone, and climate. Science, 284, 305-308.

Sudo, K., Akimoto, H. (2007) Global source attribution of tropospheric ozone: Long-range transport from various source regions. J. Geophys. Res., 112, D12302, doi:10.1029/2006JD007992

Takemura, T., Nakajima, T., Dubovik, O., Holben, B. N., Kinne S. (2002) Single-scattering albedo and radiative forcing of various aerosol species with a global three-dimensional model. J. Clim., 15, 333-352.

4.

11 MIROC20

SPRINTARS CHASERCO

5.

－ 8－－ 9－

50

CHASER 6. 6.1

(2007) (Modeling of the heterogeneous reaction processes on the polar stratospheric

clouds in chemical transport models and the effects on the Arctic ozone layer through bromine species). , 22(3), 196-203.

Akiyoshi, H., Zhou, L. B. (2007) Midlatitude and high-latitude N2O distributions in the Northern Hemisphere in early and late Arctic polar vortex breakup years. J. Geophys. Res., 112, D18305, doi:10.1029/2007JD008491.

Eyring, V., Waugh, D. W., Bodeker, G. E., Cordero, E., Akiyoshi, H., Austin, J., Beagley, S. R., Boville, B. A., Braesicke, P., Bruhl, C., Butchart, N., Chipperfield, M. P., Dameris, M., Deckert, R., Deushi, M., Frith, S. M., Garcia, R. R., Gettelman, A., Giorgetta, M. A., Kinnison, D. E., Mancini, E., Manzini, E., Marsh, D. R., Matthes, S., Nagashima, T., Newman, P. A., Nielsen, J. E., Pawson, S., Plummer, D. A., Pitari, G., Rozanov, E., Schraner, M., Scinocca, J. F., Semeniuk, K., Shepherd, T. G., Shibata, K., Steil, B., Stolarski, R. S., Tian, W., Yoshiki, M. (2007) Multi-model projections of ozone recovery in the 21st century. J. Geophys. Res., 112, D16303, doi:10.1029/2006JD008332.

Shiogama, H., Nozawa, T., Emori, S. (2007) Robustness of climate change signals in near term predictions up to the year 2030: Changes in the frequency of temperature extremes. Geophys. Res. Lett., 34, L12714, doi:10.1029/2007GL029318.

Shiogama, H., Hasegawa, A., Nozawa, T., Emori S. (2008) Changes in mean and extreme precipitation in near-term predictions up to the year 2030. SOLA, 4, 017-020, doi:10.2151/sola.2008 005.

6.2

(2007) . , 17(1), 23-28.

Eyring, V., Gettleman, A., Harris, N. R. P., Pawson, S., Shepherd, T. G., Waugh, D. W., Akiyoshi, H., Butchart, N., Chipperfield, M. P., Dameris, M., Fahey, D. W., Forster, P. M. F., Newman, P. A., Rex, M., Salawitch, R. J., Santer, B. D. (2008) Report on the 3rd SPARC CCMVal Workshop, 26-28 June 2007, University of Leeds, United Kingdom. SPARC Newsletter, 30, 17-19.

(2008) 10 (10IMSC) . , 55, 91-95.

(2008) . H19 , 46-52.

6.3

(2007) . , , 2007 10 .

(2007) CCSR/NIES. 2007 , , 2007 5 19 -24 .

Akiyoshi, H., Sakamoto, K., Nagashima, T., Imamura, T., (2007) Ozone variation in the yeras 1980-2100 calculated by the CCSR/NIES CCM in teh CCMVal REF2 scenario. IUGG 24th general assembly, July 2-13, 2007, Perugia, Italy.

(2007) . , , 2007 10 14-16 .

Akiyoshi, H., Sugata, S., Imamura, T., Nakane, H. (2008) Interannual variation in the BrO-ClO ozone destruction cycle in the northern high latitude lower stratosphere associated with the Arctic polar vortex variation in 1995-97. SMILES International Workshop, Kyoto, March 17-19 2008.

－ 8－－ 9－


(2007) . 2007 , , 2007

5 22 . (2007) 2030 2 .

, , 2007 10 . (2007) SST CO2

. , , 2007 10 . (2007)

. , , 2007 10 15 . Nagashima, T., Ohara, T., Tanimoto, H., Sugata, S., Kurokawa, J., Sudo, K., Akimoto, H., Uno, I. (2007)

Regional and global modeling of tropospheric ozone over Japan. TF HTAP Workshop on Global and Regional Modelling for Assessing Hemispheric Air Pollution, Juelich, Germany, 17 October 2007.

(2007) . 19 13 , , 2007 11 27 .

(2008) . 4

, , 2008 2 23 . (2007) 20

. , , 2007 10 . Shiogama, H., Nozawa, T., Emori, S. (2007): Robustness of climate change signals in near term predictions up

to the year 2030. 10th International Meetings on Statistical Climatology, Beijing, China, August 2007. (2007)

. , , 2007 10 . (2007)

. , , 2007 11 . Shiogama H., Stone, D., Nagashima, T., Emori, S., Nozawa, T. (2008) Additivity of temperature responses in the

global and continental scales. IDAG Spring Meeting 2008, Boulder, USA, January 2008. Shiogama, H., T. Nagashima, K. Takahashi, T. Nozawa and S. Emori (2008): Emission scenario uncertainty of

precipitation changes, 2nd Informal Workshop on Climate Risk Assessment, Yokohama, Japan, February, 2008.

(2007) . , , 2007 10 .

(2007) . , , 2007 5 16 .

Takemura, T. (2007) A study of aerosol effects on climate with a general circulation model. Yoram J. Kaufman Symposium, Greenbelt, MD, USA, May 31, 2007.

Takemura, T. (2007) Changes in cloud and precipitation formations by anthropogenic aerosols in Asian region. 24th General Assembly of the International Union of Geodesy and Geophysics (IUGG2007), Perugia, Italy, July 5, 2007.

Takemura, T. (2007) A Study of aerosol effects on climate with a general circulation model and satellite observations. Gordon Research Conference: Radiation and Climate. New London, NH, USA, August 3, 2007.

Takemura, T. (2007) Simulation of aerosol effects on climate system in Asia. A-Train Symposium, Lille, France, October 25, 2007.

Takemura, T. (2008) Aerosol effects on climate system simulated by aerosol climate model. JSPS-DFG Round Table on 'Climate System Research Status and Perspective', Hamburg, Germany, January 16, 2008.

Yamashita, Y., Sakamoto, K., Akiyoshi, H., Zhou, L. B., Nagashima, T., Takahashi, M. (2007) Solar cycle, QBO effect to the stratosphere and troposphere. Spring AGU/Joint Assembly 2007 Meeting. Acapulco, Mexico, 2007.5.22-25.

Yamashita, Y., Takahashi, M. (2007) Solar cycle modulation of wave forcing over troposphere related to the annular mode over stratosphere. Chapman Conference on The Role of the Stratosphere in Climate and Climate Change, Santorini, Greece, 2007.9.24-28.

Yamashita, Y., Takahashi, M. (2007) Solar cycle modulation of wave forcing over troposphere related to the annular mode over stratosphere. International CAWSES Symposium, Kyoto, Japan, 2007.10.23-27.

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6.4 (2007) , 3 .

, No.26, 16pp. 7.

305-8506 16-2

Tel: 029-850-2898 Fax: 029-850-2960 E-mail: [email protected]

－ 10 －－ 11 －


Project name: Improvement of Atmospheric Chemistry- and Aerosol-Related Processes in the Climate Model and its Verification with the Simulation of Past and Present Climate 2007 April - 2010 March Project leader: Tatsuya NAGASHIMA, National Institute for Environmental Studies Project members: Toru NOZAWA, Hideharu AKIYOSHI, Yukiko YAMADA, Hideo SHIOGAMA, Yosuke YAMASHITA, National Institute for Environmental Studies Toshihiko TAKEMURA, Kyushu University Kengo SUDO, Nagoya University Masaaki TAKAHASHI, Michio HIRENZAKI, Center for Climate System Research, The University of Tokyo Zhou LIBO, Chinese Academy of Science Abstract:

An Earth system model (ESM) which includes atmospheric chemical and aerosol processes and oceanic and terrestrial carbon cycles is in development as a collaborative effort by the National Institute for Environmental Studies (NIES); Center for Climate System Research (CCSR), The University of Tokyo; Frontier Research Center for Global Change (FRCGC); and other institutes. Our project was launched to cover the development of atmospheric chemistry and aerosol processes in the ESM. Our goal is to introduce the sophisticated treatment of both processes into the ESM, and tune the model through the simulation of climate and atmospheric environments in the recent past. Another goal of the project is to carry out climate studies using the existing models that comprise the ESM.

In this fiscal year, we extended the top of the model to stratopause height (about 80 km) for the inclusion of the stratospheric chemistry process and increased the number of vertical layers in the model. Gas phase chemical reactions involving chlorine and bromine species, which are important for the stratospheric chemistry, were introduced in the model. The reactions were chosen referring to those in the stratospheric chemistry climate model of CCSR/NIES (CCSR/NIES CCM). Comparison of the calculated distribution of chlorine and bromine species in the stratosphere with those calculated from the CCSR/NIES CCM showed that our ESM can properly simulate the chlorine species distribution, which is consistent with CCSR/NIES CCM calculation, but consistency in the estimation of bromine species was low; further tuning to the model is necessary.

Several climate studies have been carried out using these existing models. These include 1) source analysis of the tropical lower stratospheric ozone variation synchronized with the 11 year variation in the solar insolation with the CCSR/NIES CCM, 2) verification of the additivity of climate responses to different climate forcings through a large number of different scenario experiments with an atmosphere-ocean general circulation model, 3) the establishment and data archiving of a global aerosol forecasting system based on a tropospheric aerosol transport model, and 4) source attribution study of an “event level” increase of CO observed in the Alaska region based on a tropospheric chemistry transport model and utilizing a tagged tracer transportation experiment.

Keywords: Earth system model, Atmospheric chemistry, Atmospheric aerosols

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30

GCM “MIROC”

ENSO phase

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3

MIROCENSO

GCM

IPCC 5 100

GCM “MIROC”

3.3

MIROCT42 2.8 20 1.4 x 0.5-1.4 ,

44 IPCC 4MIROC “MIROC-medres” 3.2

a bc a - c

3.4 3.4.1

1 GCM 0-700 m 50

Ishii et al., 2003, 2006

MIROC’A’ ’B’ 20 ENSO

8 B

MIROC BGM Toth and Kalnay, 1993

BGM

2 ENSO

ENSO

MIROC Utopia-QuickestSecond-Order-Moment

－ 16 －－ 17 －

-ENSO 20

30 0-700 m

3.4.2

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CO2 i ii CO2 iii3

Bony et al. 2004

SST30 CO2

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1

Yokohata et al., 2005

GCMslab ocean

ASGCM Slab oceanASGCM AOGCM

ASGCM

2

MIROCWilson and Ballard 1999, WB99

WB99 MIROCWB99

WB99 ab 1

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Bony, S., Dufresne, J.L., LeTreut, H., Morcrette, J.J., Senior, C.A. (2004) On dynamic and thermodynamic components of cloud changes. Clim., Dyn. 22, 71-86.

Ishii, M., Kimoto, M., Kachi, M. (2003) Historical ocean subsurface temperature analysis with error estimates. Mon. Weath. Rev., 131, 51-73.

Ishii, M., Kimoto, M., Sakamoto, K., Iwasaki, S. (2006) Steric sea level changes estimated from historical ocean subsurface temperature and salinity analysis. J. Oceanogr., 62(2), 155-170.

Meehl, G., Hibbard, A.K., session participants (2006) Earth System Models: The Next Generation, Report from Aspen Global Change Institute session.

Toth, Z., Kalnay, E. (1993) Ensemble forecasting at NMC – The generation of perturbations. Bull. Am. Met. Soc., 74(12), 2317-2330.

Yokohata, T., Emori, S., Nozawa, T., Tsushima, Y., Ogura, T., Kimoto, M. (2005) Climate response to volcanic forcing: Validation of climate sensitivity of a coupled atmosphere-ocean general circulation model. Geophys. Res. Lett., 32, L21710, doi:10.1029/2005GL023542.

Wilson, D. R., Ballard, S.P. (1999) A microphysically based precipitation scheme for the UK Meteorological Office Unified Model. Q.J.R. Meteorol. Soc., 125, 1607-1636.

4.

MIROC ENSO ENSO

ENSOMIROC

CO2

30ASGCM

AOGCM ASGCMMIROC

phase

1

－ 18 －－ 19 －

大気海洋結合モデルの物理過程改良および気候変化予測の手法開発

5. 今後の研究展望 ENSO の再現性向上を目指して引き続き MIROC の物理・力学過程の精緻化を行う。また、成長

モード育成法による初期摂動の作成において計算コストを抑えられるよう改良を加える。この改

良により、多数の初期摂動を用いたアンサンブル予報実験が可能となる。温暖化に伴う降水変化

のメカニズムを理解するために数値実験を引き続き行う。また解析対象を平均降水量だけでなく

豪雨の頻度等に広げる。ピナツボ火山噴火再現実験については、AOGCM と同様の結果を再現で

きるよう調整した ASGCM を用いてアンサンブル実験を開始する。MIROC に導入した雲氷予報ス

キームについては詳細な性能評価とチューニングを行い、必要に応じて雲微物理過程に修正を加

える。 6. 研究成果発� 6.1 誌上発��読�� Arai, M., Kimoto, M. (2007) Simulated interannual variation in summertime atmospheric circulation associated

with the East Asian monsoon. Climate Dyn., doi 10.1007/s00382-007-0317-y. Hirabayashi, Y., Kanae, S., Emori, S., Oki, T., Kimoto, M., Takeuchi, K. (2008) Global projections of changing

risks of floods and droughts in a changing climate. Hydrolog. Sci. J., 53(4), 754-772. Inatsu, M., Kimoto, M. Sumi, A. (2007) Stratospheric sudden warming with projected global warming and

related tropospheric wave activity. SOLA, 3, 105-108. Ogura, T., Emori, S., Web, M. J., Tsushima, Y., Abe-Ouchi, A., Kimoto, M. (2008) Towards understanding

cloud response in atmospheric GCMs: the use of tendency diagnostics. J. Meteor. Soc. Japan, 86(1), 69-79. Saito, K., Kimoto, M., Zhang, T., Takata, K., Emori, S. (2007) Change in hydro-thermal regimes in the

soil-freezing regions under the global warming simulated by a high-resolution climate model. J. Geophys. Res.-Earth Surface, 112 (F2): Art. No. F02S11 JUN 20 2007.

Takayabu, Y. N., Kimoto, M. (2008) Diurnal march of rainfall simulated in a T106 AGCM and dependence on cumulus schemes. J. Meteor. Soc. Japan, in press.

Yokohata, T., Emori, S., Nozawa, T., Ogura, T., Kawamiya, M., Tsushima, Y., Suzuki, Ta., Yukimoto, S., Abe-Ouchi, A., Hasumi, H., Sumi, A., Kimoto, M. (2008) Comparison of equilibrium and transient responses to CO2 increase in eight state-of-the-art climate models. Tellus, A, 60 (5), 946-961, doi:10.1111/j.1600-0870.2008.00345.x

6.2 誌上発��読�� 木本昌秀 (2007) High-impact weather: 今後の研究の展望. 日本気象学会誌「天気」, 54(7), 635-638. 木本昌秀 (2007) 将来の気候変化に関する予測. 特集「地球温暖化を読む」, 科学, 77(7), 696-701. 木本昌秀 (2007) 異常気象と温暖化の関係とは―熱波、豪雨、干ばつ．．．地球温暖化が気象の極端化

に与える影響は大. 日本の論点. 文藝春秋編, 648-651. 6.3 ��発� Arai, M. (2007) Influence of aerosols and green house gasses on the change in the Asian monsoonal

precipitation. International Workshop on Semi-Arid Land Surface-Atmosphere Interaction, 9-13 Augusut, 2007, Lanzhou, China.

荒井美紀・宮坂貴文・野沢徹・木本昌秀 (2007) アジアモンスーン域夏季降水に対するエアロゾルの影

響. 2007 年日本気象学会秋季大会講演予稿集, A115. Arai, M., Miyasaka, T., Nozawa, T., Nagashima, T., Kimoto, M. (2007) Influence of aerosols and green house

gasses on the change in the Asian monsoonal precipitation. Joint Conference on the 6th International Symposium on Asian Monsoon System and the 9th East Asian Climate Workshop, 10-13 December, 2007, Fukuoka, Japan.

長谷川聡・江守正多・塩竈秀夫・三浦裕亮 (2007) 水惑星実験における SST と CO2 濃度の変化による

降水の力学・熱力学的変化. 日本気象学会秋季大会, 2007 年 10 月. Imada, Y. Kimoto, M. (2007) A Role of the South Pacific in the Tropical Pacific Decadal Variability. University

Allied Workshop 2007, June 18-20, 2007, Beijing, China. 今田由紀子・木本昌秀(2007) 大気海洋結合大循環モデルに見られる数十年規模の ENSO の変調. 2007

年日本気象学会秋季大会講演予稿集, P392.

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(2007) . 2007 , A208.

7.

305-8506 16-2


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Project name: Improvement of Physical Processes in the Ocean Atmosphere Coupled GCM and Development of Climate Prediction Technique 2007 April - 2010 March Project leader: Tomoo OGURA, National Institute for Environmental Studies Project members: Masahide KIMOTO, Center for Climate System Research, The University of Tokyo Seita EMORI, Akira HASEGAWA, Tokuta YOKOHATA, National Institute for Environmental Studies Hiroyasu HASUMI, Yukari TAKAYABU, Yoshimitsu CHIKAMOTO, Miki NONAKA- ARAI, Yukiko IMADA-KANAMARU, Center for Climate System Research, The University of Tokyo Abstract:

The need for a near-term prediction of climate extremes and reducing the uncertainty in climate prediction has been highlighted in recent years when evaluating the socio-economic impact of global warming. This study attempts to fill the need by developing expertise in the near-term climate prediction and reducing uncertainty in climate prediction by improving the physical/dynamical processes in an ocean atmosphere coupled GCM 'MIROC' and conducting numerical experiments with the GCM. At the beginning phase of the project, the ocean advection and cloud microphysics schemes have been updated, which led to better representation of ENSO amplitude and thermodynamic phase of cloud condensate in the model. Numerical experiments have been conducted to understand the mechanism of precipitation changes due to global warming. Preliminary runs have also been conducted to handle some technical issues regarding an ensemble experiment for the near-term prediction and the simulation of climate change due to a volcanic eruption. Keywords: Global warming, Ocean-atmosphere coupled model, Predictability, Climate sensitivity

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19 CGER-I086-2008, CGER/NIES

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19 19

1.

2.

2.1 CPU Total 0hr

2.2

MRI MRI-CCM

193.4

3.

3.1(CCM Validation) Eyring et al., 2005

19602100

3.2

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1987

CCly 199360S-60N

1993 WMO, 20071990

CCM

WMO, 2007 CCM2060

CCM CCly (Eyring et al., 2007) CCM

3.3

MRI-CCM Shibata et al., 2005T42 2.8

300 km 68 80 km [0.0 1hPa] T42L68 QBO

68150 hPa 100 hPa 1 hPa 500 m 0.05 hPa

7 36 15 80 352 PSC

PSC 6 3

3.4WMO, 2007 Eyring

et al.(2006) MRI-CCM QBO/ ENSO Shibata and Deushi 2008)

WMO 201019

CCMVal

3 4

QBO

QBO 2 3 QBOQBO

CCMVal 4

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REF-B0 2000 20 REF-B1 1960-2006 REF-B2 1960-2100 CTL-B0 1960 20

Eyring V., Harris, N. R. P., Rex, M., Shepherd, T. G., Fahey, D. W., Amanatidis, G. T., Austin, J., Chipperfield, M.

P., Dameris, M., Forster, P. M. De F. (2005) A strategy for process-oriented validation of coupled chemistry-climate models, Bull. Am. Meteorol. Soc., 86, 1117– 1133.

Eyring, V., Butchart, N., Waugh, D. W., Akiyoshi, H., Austin, J., Bekki, S., Bodeker, G. E., Boville, B. A., Bruhl, C., Chipperfield, M. P. (2006) Assessment of temperature, trace species and ozone in chemistry-climate model simulations of the recent past. J. Geophys. Res., 111, D22308, doi:10.1029/2006JD007327.

Eyring, V., Waugh, D. W., Bodeker, G. E., Cordero, E., Akiyoshi, H., Austin, J., Beagley, S. R., Boville, B. A., Braesicke, P., Bruhl, C. (2007) Multimodel projections of stratospheric ozone in the 21st century. J. Geophys. Res., 112, D16303, doi:10.1029/2006JD008332.

Shibata, K. K., Deushi, M., Sekiyama, T. T., Yoshimura, H. (2005) Development of an MRI chemical transport model for the study of stratospheric chemistry. Papers in Geophysics and Meteorology, 55, 75-119.

Shibata, K., Deushi, M. (2008) Long-term variations and trends in the simulation of the middle atmosphere 1980-2004 by the chemistry-climate model of the Meteorological Research Institute. Annales Geophysicae, 26, 1299-1326.

World Meteorological Organization (WMO), Scientific Assessment of Ozone Depletion: 2006. World Meteorological Organization, Global Ozone Research and Monitoring Project, Report No.50, Geneva, Switzerland, 2007.

4.

(CCM Validation)MRI-CCM

1960 452100 140

WMO/UNEP2010

5.

6.

305-0052 Tel: 029-853-8710 Fax: 029-855-7240 E-mail: [email protected]

－ 24 －－ 25 －


Project name: Analysis of Long-term Variations in the Ozone Layer Destruction and Prediction of the Ozone Layer under Global Warming Scenarios 2007 April - 2008 March Project leader: Kiyotaka SHIBATA, Atmospheric Environment and Applied Meteorology Research Department, Meteorological Research Institute Abstract:

The ozone depleting substances such as chlorofluorocarbons and halons are decreasing, or at least their increasing rates are decreasing, owing to the prevalence of the Montreal Protocol, its adjustments and amendments. However, in recent years the ozone hole in the Antarctic does not seem to be diminishing, and the future projection of the ozone layer and ozone depleting substances is not necessarily well known in detail. To address these issues, hindcast experiments of a chemistry-climate model are carried out and the factors responsible for long-term variations in the ozone layer are analyzed. In addition, scenario-based experiments of future projection for the ozone layer are also performed to investigate quantitatively when the ozone layer will recover to its pre-1980 state, and how global warming due to increased greenhouse gasses affects the ozone layer. Keywords: Chemistry-climate model, Ozone depletion, Greenhouse gas, Global warming, Future prediction of the ozone layer

－ 27 －

－ 27 －


MIROC

GCMGCM

1 2MIROC

19 MIROCMATSIRO

H07 MIROC MATSIRO

0.08K 0.2%

－ 28 －－ 29 －

MIROC

MIROC

19 21

1.

GCMGCM

1 2CCSR/NIES/FRCGC MIROC

19 MIROCMATSIRO

2. 2.1

CPU Total 1,764hrs 2.2

MATSIRO

PC

3. 3.1

H07 Hanasaki et al., 2007a,b MIROCMATSIRO

0.08K0.2%

3.2

2.5×106 km2 1100-1800 km3

－ 28 －－ 29 －


GCMBoucher et al., 2004 Lobell et al.,

2006a,b H07 Hanasaki et al., 2007a,bMIROC

3.3

T42 MIROC AGCM5.7b slab oceanMATSIRO MATSIRO

H07

MATSIRO 2

Döll and Siebert 2000 1990Hanasaki et al., 2007a,b

1 m 75%2

5 1 ICU25 10

15

1

CTL -- --

IAS

IAU

ICS

ICU

3.4

19 MIROC 2

75%ICU

830 km3 1090-1320 km3

20

34

IAS, IAU, ICS, ICU CTL ICU0.08K 0.2%0.16K 1.5%

－ 30 －－ 31 －

MIROC

120

2

(km3 yr-1) (km3 yr-1) IAS 1170 520 44%IAU 1170 1170 100%ICS 830 300 36%ICU 830 830 100%[Döll and Siebert, 2002] 1090 (1st and 2nd crop) -- --[Hanasaki, et al., 2007b] 1200 (1st and 2nd crop) 460 38%[Jachner, et al., 2007] 1320 (1st and 2nd crop) 610 46%

3 CTL

(%) (%) (K) (%)

IAS +0.2/+0.6 +0.3/+0.4 +0.06/+0.10 +0.2/-0.1

IAU 0.0/+2.1 -1.0/-0.5 -0.15/-0.24 0..0/+0.9

ICS +0.2/+0.7 +0.1/+0.1 +0.04/+0.02 +0.2/+0.4

ICU +0.2/+2.0 -0.3/+0.4 -0.08/-0.16 +0.2/+1.5

1 CTL

－ 30 －－ 31 －


Boucher, O., Myhre, G., Myhre, A. (2004) Direct human influence of irrigation on atmospheric water vapour and climate. Clim. Dyn., 22, 597-603.

Döll, P., Siebert, S. (2000) A digital global map of irrigated areas. ICID J., 49, 55-66. Döll, P., Siebert, S. (2002) Global modeling of irrigation water requirements. Water Resour. Res., 38, 1037,

doi:10.1029/2001WR000355. Hanasaki, N., Kanae, S., Oki, T., Masuda, K., Motoya, K., Tanaka, K. (2007a) An integrated model for

assessment of global water resources. Part 1: Input meteorological forcing and natural hydrological cycle modules. Hydrol. Earth Syst. Sci. Discuss., 4, 3535-3582.

Hanasaki, N., Kanae, S., Oki, T., Shirakawa, N. (2007b) An integrated model for assessment of global water resources. Part 2: Anthropogenic activities modules and assessments. Hydrol. Earth Syst. Sci. Discuss., 4, 3583-3626.

Rost, S., Gerten, D., Bondeau, A., Lucht, W., Rohwer, J., Schaphoff, S. (2008) Agricultural green and blue water consumption and its influence on the global water system. Water Resour. Res., 44, W09405, doi:10.1029/2007WR006331.

Lobell, D. B., Bala, G., Bonfils, C., Duffy, P. B. (2006a) Potential bias of model projected greenhouse warming in irrigated regions. Geophys. Res. Lett., 33, L13709.

Lobell, D. B., Bala, G., Duffy, P. B. (2006b) Biogeophysical impacts of cropland management changes on climate. Geophys. Res. Lett., 33, L06708.

4.

MIROC H07

0.08K 0.2% 5.

6. 6.1 Hanasaki, N. (2008) H07-MIROC coupled model -Assessing impact of irrigation on climate. 2nd Workshop on

Climate Risk Assessment, Yokohama, 12-13 Feb. 2008. 7.

305-8506 16-2


－ 32 －－ 33 －

MIROC

Project name: Improvement of the Land Surface Process of MIROC Global Climate Model and its Application to Land-Atmosphere Interaction Studies 2007 April - 2010 March Project leader: Naota HANASAKI, National Institute for Environmental Studies Project members: Akihiko ITO, National Institute for Environmental Studies Taikan OKI, Shinjiro KANAE, Tomohito YAMADA, Nobuyuki UTSUMI, Dai YAMAZAKI, Institute of Industrial Science, The University of Tokyo Abstract:

Due to rapid increase in the spatial/temporal resolution of global climate models (GCMs) and increasing sophistication of climate change research, the land-atmosphere/land-ocean feedback is beginning to play a more important role in climate simulations. Therefore, it is an urgent issue for GCM developers to improve the land process of GCMs. This project aims to improve the land processes of MIROC, a GCM, focusing on 1) land surface process (heat and water balance) and 2) processes of ecological change and carbon cycles. In the fiscal year 2007, we incorporated the irrigation process to the MATSIRO (the land surface model of MIROC), which is one of major anthropogenic activities in global hydrological cycle.

The irrigation scheme of the H07 model (an integrated global water resources model) was implemented to the MIROC global climate model. This new model enables us to represent irrigation in a global climate model, controlling the soil moisture in the irrigated cropland during the cropping period. In order to assess the impact of irrigation on the global climate system, a series of simulations was conducted using the super computer of the National Institute for Environmental Studies, Japan. Estimated annual global irrigation water requirement was 830km3, which is fairly comparable to several earlier studies. The results show that irrigation decreased the global mean temperature by 0.08K and increased precipitation by 0.2%. These successful results encourage us to further develop earth system modeling incorporating major human activities. Keywords: Land surface process, Ecological change, Carbon cycle

－ 32 －－ 33 －


MIROC

MIROC IPCC 4

MIROC

MIROC

MIROC

－ 34 －－ 35 －

MIROC

MIROC

19 19

1.

MIROC NPDZLPJ

MIROC 2. 2.1


IPCC 4 IPCC, 2007MIROC3.2

3. 3.1

IPCC 4

3.2

－ 34 －－ 35 －


Edwards et al., 20072 1

Hargreaves et al., 2007

CCSR/NIES/FRCGC MIROC3.2

3.3

IPCC 4 MIROC3.2 T42 ”medres” versionCTRL 2xCO2

LGMLGMGHG LGM 2xCO2

LGMGHG 2xCO2

LGMGHG LGM LGMTwo-sided Partial Radiative Perturbation

PRPCTRL

Wetherald and Manabe, 1988; Colman and McAvaney, 1997

e.g., Yoshimori and Broccoli, 2008 PRP

Cloud Radiative Forcing CRFCess and Potter, 1988 Approximate PRP APRP Taylor et al., 2007 Yokohata et al. 2005

3.4

MIROC3.2 Tett et al. 2002

Stuber et al. 2001

2xCO2 LGMGHG LGM 1 2

－ 36 －－ 37 －

MIROC

1 2xCO2 LGMGHG LGM GHGs orbit

-1

-0.5

0

0.5

1

1.5

2

2.5

3

ALLSUMCLDLCLDSALBWV+LRLRWV

Feed

back

str

engt

h (W

m-2

K-1

)

2xCO2

LGMGHGLGM

2 2xCO2 LGMGHG LGM WV LR ALB CLDS CLDLWV+LR

SUMALL +/-1

2xCO2 LGMGHG LGM2xCO2 LGM

LGM2xCO2

2xCO2 LGMGHGLGM

－ 36 －－ 37 －


LGM

LGM2xCO2

2xCO2

LGMGHG LGM 2xCO2 LGM

2xCO2

LGM

APRP PRP

LGMCRF Yokohata et al., 2005

PRP

Cess, R. D., Potter, G. L. (1988) A methodology for understanding and intercomparing atmospheric climate

feedback processes in general circulation models. J. Geophys. Res., 93(D7), 8305-8314. Colman, R. A. and B. J. McAvaney (1997) A study of general circulation model climate feedbacks determined

from perturbed sea surface temperature experiments. J. Geophys. Res., 102(D16), 19,383-19,402. Edwards, T. L., M. Crucifix, and S. P. Harrison (2007) Using the past to constrain the future: how the

palaeorecord can improve estimates of global warming. Prog. Phys. Geog., 481-500, DOI:10.1177/0309133307083295.

Hargreaves, J. C., Abe-Ouchi, A., Annan, J. D. (2007) Linking glacial and future climates through an ensemble of GCM simulations. Clim. Past, 3, 77-87.

IPCC (2007) Climate Change 2007: The physical science basis. Contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor and H. L. Miller (eds.)] Cambridge University Press, Cambridge, U.K. and New York, NY, USA, 996pp.

Stuber, N., Ponater, M. Sausen, R. (2001) Is the climate sensitivity to ozone perturbations enhanced by stratospheric water vapor feedback? Geophys. Res. Lett., 28(15), 2887-2890.

Taylor, K., Crucifix, E., M., Braconnot, P., Hewitt, C. D., Doutriaux, C., Broccoli, A. J., Mitchell, J. F. B.,. Webb, M. J. (2007) Estimating shortwave radiative forcing and response in climate models. J. Climate, 20(11), 2530-2543.

Tett, S. F. B., Jones, G. S., Stott, P. A., Hill, D. A., Mitchell, J. F. B., Allen, M. R., Ingram, W. J., Johns T. C., Johnson, C. E. Jones, A., Roberts, D. L., Sexton D. M. H., Woodage, M. J. (2002) Estimation of natural and anthropogenic contributions to twentieth century temperature change. J. Geophys. Res., 107(D16), 4306, 10.1029/2000JD000028.

Wetherald, R. T. and S. Manabe (1988) Cloud feedback processes in a general circulation model. J. Atmos. Sci., 45(8), 1397-1415.

Yokohata, T., Emori, S., Nozawa, T., Tsushima, Y., Ogura, T., Kimoto, M. (2005) Climate response to volcanic forcing: Validation of climate sensitivity of a coupled atmosphere-ocean general circulation model. Geophys. Res. Lett., 32, L21710. DOI:10.1029/2005GL023542.

Yoshimori, M., Broccoli, A. J. (2008) Equilibrium response of an atmosphere-mixed layer ocean model to different radiative forcing agents: global and zonal mean response. J. Climate, 21(17), 4399-4423.

－ 38 －－ 39 －

MIROC

4.

5.

MIROC

SPRINTARS

6. 6.1 Yoshimori, M., Broccoli, A. J. (2008) Equilibrium response of an atmosphere-mixed layer ocean model to

different radiative forcing agents: global and zonal mean response. J. Climate, 21(17), 4399-4423. Abe-Ouchi, A., Segawa, S., Saito, F. (2007) Climatic Conditions for modelling the Northern Hemisphere ice

sheets throughout the ice age cycle. Clim. Past, 3 , 423-438. Otto-Bliesener, B..L, Hewitt, C..D., Marchitto, T..M., Brady, E., Abe-Ouchi, A., Crucifix, M., Murakami, S., .

Weber, S..L. (2007) Last Glacial Maximum Ocean Thermohaline Circulation: PMIP2 Model Intercomparisons and Data Constraints. Geophys. Res. Lett., 34, L12706, doi:10.1029/2007GL029475

Yanase, W., Abe-Ouchi, A. (2007) The LGM surface climate and atmospheric circulation over East Asia and the North Pacific in the PMIP2 coupled model simulations. Clim. Past, 3, 439-451.

(2007) , 54(12), 995-998.

7.

277-8568 5-1-5

TEL: 04-7136-4405 FAX: 04-7136-4375 E-mail: [email protected]

－ 38 －－ 39 －


Project name: Paleoclimate Modeling and Global Warming Experiments Using MIROC–Med and an Ice Sheet Model (ICIES) 2007 October - 2008 March Project leader: Ayako ABE-OUCHI, Center for Climate System Research, The University of Tokyo Project members: Masakazu YOSHIMORI, Akira OKA, Ryouta O’ISHI, Megumi CHIKAMOTO, Yuki OKADA, Megumi KOJIMA, Ryutaro KIMURA, Hironori ICHIJO, Tomoyuki IDE, Center for Climate System Research, The University of Tokyo Abstract:

The coupled atmosphere-ocean general circulation models are used for the future climate projections. The MIROC model, one of such state of the art models, has contributed to the IPCC fourth assessment report. Recently it is widely recognized that it is important to incorporate the feedback effect of terrestrial and marine carbon cycles and vegetation changes on climate change into predictions of the future. In addition, it is becoming more important to drive ice sheet models with high accuracy or to couple climate and ice sheet models in association with projections of future sea level change. In this study, we make an attempt to understand and evaluate the feedback process quantitatively, which is one of the largest uncertainties for the above applications.

Climate sensitivity, a useful metric that represents the gross size of the climate system response, is determined by radiative feedback processes. We investigated such feedback processes operating in the MIROC model. In addition, we explored the possibility of utilizing paleoclimatic information in constraining estimations of climate sensitivity for the future. Climate sensitivity is an important parameter which affects carbon cycles, vegetation changes, and ice sheet model behaviors. The study was accomplished by comparing feedback processes operating among doubled carbon dioxide, last glacial maximum (LGM) experiments, and the experiment with LGM greenhouse gas forcing. The difference in climate sensitivity among the experiments is attributed to the difference in the shortwave cloud feedback strength, rather than water vapor, lapse rate, and albedo feedbacks. This suggests that care must be exercised when simple scaling of the past climate sensitivity to the future is applied, but the range of current intermodel climate sensitivities is much larger than the difference in the climate sensitivity between the experiments conducted in the present study. Therefore, the active use of paleoclimatic information for future projections is encouraged. Furthermore, simplified feedback analysis methods were examined with respect to the supposedly the most accurate method that was used in the analysis above. These tools will be useful in understanding a range of response that various models produce, and in evaluating associated uncertainties for carbon cycle, vegetation, and ice sheet changes. Keywords: MIROC climate model, Climate sensitivity, Ice sheet model, Carbon cycle model

－ 41 －

－ 41 －


wave-CISK

－ 42 －－ 43 －

16 19

1.

2

2. 2.1

CPU Total 0hr

2.2 2

3

3. 3.1

100 1

3.5 km NICAM

2

Emanuel, 1987

－ 42 －－ 43 －


wave-CISK Hayashi, 1970 Nakajima, 2004; Nakajima, 2005

wave-CISK

, 20083

20

Hayashi et al., 2005; , 2008

Nakajima et al. 2007wave-CISK

wave-CISK

Nakajima et al., 2006

3.2

22 km 600

m

32,768 km 23 km 80

－ 44 －－ 45 －

3.3 40

1 45

－ 44 －－ 45 －


－ 46 －－ 47 －

3.4 Nakajima et al. 2007 wave-CISK

Pauluis and Held, 2002

Emanuel, K.A. (1987) An air-sea interaction model of intraseasonal oscillations in the Tropics. J. Atmos. Sci., 44, 2324-2340.

Emanuel. K.A., Neelin, J.D., Bretherton, C.S. (1994) On large-scale circulations in convecting atmospheres. Quart. J. Roy. Meteorol. Soc., 120, 1111-1143.

Hayashi, Y. (1970) A theory of large-scale equatorial waves generated by condensation heat and accelerating the zonal wind, J. Meteorol. Soc. Japan, 48, 140-160.

Hayashi, Y.-Y., Odaka, M., Yamada, Y., Morikawa, Y., Ishiwatari, M., Nakajima, K., Takehiro, S. (2005) An aqua-planet experiment on structurization of equatorial precipitation activity and related software development toward an atmospheric general circulation model for terrestrial planets. CGER's Supercomputer Activity Report, National Institute for Environmental Studies, Vol. 12-2003, 77-86.

(2008) . 18 , 65-72.

Nakajima, K. (2004) Ultra-high resolution modeling of the tropical air-sea interaction: Natural variability in large domain cloud resolving model. CGER’s Supercomputer Activity Report, National Institute for Environmental Studies, Vol. 11-2002, 49-54.

Nakajima, K. (2005) Ultra-high resolution modeling of the tropical air-sea interaction: Spontaneous concentration of cloud activity in “planetary” scale. CGER’s Supercomputer Activity Report, National Institute for Environmental Studies, Vol. 12-2003, 61-67.

Nakajima, K., Odaka M., Sugiyama, K., Kitamori, T. (2006) Numerical experiment on the interaction between large-scale atmospheric motion and cumulus convection: Preferred scale of the planetary-scale concentration of cloud activity and new model development. CGER’s Supercomputer Activity Report, National Institute for Environmental Studies, Vol. 13-2004, 69-76.

Nakajima, K., Odaka M., Sugiyama, K., Kitamori, T. (2007) Numerical experiment on the interaction between large-scale atmospheric motion and cumulus convection: Mechanism of spontaneous large-scale stationary concentration of cloud activity. CGER’s Supercomputer Activity Report, National Institute for Environmental Studies, Vol. 14-2005, 55-60.

(2008) . 18 , 91-95.

Pauluis, O., Held, I.M. (2002) Entropy budget of an atmosphere in radiative-convective equilibrium. Part I.: Maximum work and frictional dissipation. J. Atmos. Sci., 59, 125-239.

－ 46 －－ 47 －


4.

wave-CISK

5.

6. 6.1

(2007) Vol.22, 101-106. 6.2 Nakajima, K., Odaka, M., Sugiyama K., Kitamori, T., (2007) Numerical experiment on the interaction between

large-scale atmospheric motion and cumulus convection: mechanism of spontaneous large-scale stationary concentration of cloud activity. CGER's supercomputer activity report, vol.14-2005, 55-60.

6.3

(2007) 3. 2007 , 2007 9 .

(2007) . 2007 , , 2007 10 .

(2007) 3. 2007 , 2007 10 .

6.4

deepconv: A two-dimensional non-hydrostatic fluid model. http://www.gfd-dennou.org/library/deepconv/ .

7.

812-8581 6-10-1


－ 48 －－ 49 －

Project name: Direct Numerical Experiment on the Interaction between Cumulus Convection and Large-Scale Atmospheric Motions 2004 April - 2008 March Project leader: Kensuke NAKAJIMA, Faculty of Sciences, Kyushu University Project member: Masatsugu ODAKA, Graduate School of Science, Hokkaido University Abstract:

In this study, we investigate the interaction between cumulus convection and large-scale atmospheric motions by using a very large two-dimensional domain cumulus resolving model. By comparing the results of the present experiments with those of experiments with cumulus parameterization, we hope to clarify deficiencies and possible directions of improvement in cumulus parameterizations.

The structure of large-scale disturbance associated with the planetary-scale concentration of cloud activity appearing spontaneously without wind evaporation feedback remained unclear in our research last year, and so we scrutinized it this year. The results imply that an essential component of the disturbance is a large amplitude upper tropospheric temperature anomaly. This temperature anomaly presumably results from radiative cooling in the upper troposphere, which agrees with the results of parameter studies that show that this kind of spontaneous organization of clouds occurs only with strong radiative cooling in the upper troposphere. The present result is superior to previous interpretations based on wave-CISK in several aspects. Moreover, it suggests a way to clarify large-scale cloud structure in the framework of thermodynamics of the atmosphere. For further confirmation, more quantitative examination of the results is necessary, including cases in which weak or no cloud concentration is observed.

In the future, we are planning to develop a framework with which the interaction between cloud resolving models and the GCM can be represented more easily and more rigorously, in more explicit collaboration with the GCM development group in GFD-Dennou Club.

Keywords: Non-hydrostatic model, Cumulus parameterization, Interaction between cumulus convection and large-scale atmospheric motions, Radiative cooling

－ 48 －－ 49 －


NICAM

NICAM

360 km NICAM

2004 2006 5 200621 3

2

－ 50 －－ 51 －

NICAM

NICAM

19 19

1.

NICAM Nonhydrostatic ICosahedral Atmospheric Model; Satoh et al., 2008 km km

CREST Core Research for Environmental Science and TechnologyMJO Madden Julian

Oscillation

2. 2.1

CPU Total 6,581hrs

2.2 NICAM

60 km

3. 3.1

3NICAM 60 km

2004 2006 52006 21 3

2

－ 50 －－ 51 －


3.2

Rotunno and Emanuel, 1987

Ritchie and Holland, 1999

3.3 60 km

NICAM NICAM

Arakawa-Schubert Reynolds 1

32004 2006 5

1 60 km NICAM 0621 OLR Outgoing Longwave Radiation; 2006 11 25 150E 2

11 30

－ 52 －－ 53 －

NICAM

3.4 2004 2006 5 3 04180423 0613 1 05142 0621 3 0621

12 3

06214 14 km

0621

2005 14 2

Ritchie, E., Holland, G. J. (1999) Large-scale patterns associated with tropical cyclogenesis in the western Pacific. Mon. Wea. Rev., 127, 2027-2043.

Rotunno, R., Emanuel, K. A. (1987) An air-sea interaction theory for tropical cyclones. Part II: Evolutionary study using a nonhydrostatic axisymmetric numerical model. J. Atmos. Sci., 44, 542-561.

Satoh, M., Matsuno, T., Tomita, H., Miura, H., Nasuno, T., Iga, S. (2008) Nonhydrostatic Icosahedral Atmospheric Model (NICAM) for global cloud resolving simulations. J. Comput. Phys, 227, 3486-3514.

4.

60 km NICAM2004 2006 5 3

2006 21

2 0621 OBS; 4 11 22 12UTC I22; 6 11 20 12UTC

I20; 60 km G07; 14 km G09; 7 km G10; 60 km 14 km

－ 52 －－ 53 －


14 km

5.

3

30 60 km

6. 6.1 Satoh, M. (2008) Numerical simulations of heavy rainfalls by a global cloud-resolving model. J. Disaster Res., 3,

33-38. 6.2

NICAM (2007) 20 NICAM . 9, .

Satoh, M. (2007) A Madden-Julian Oscillation event realistically simulated by a global cloud-resolving model. Met Office.

NICAM (2007) . .

Satoh, M. (2007) A global cloud-resolving atmospheric model in Japan. SLOAN workshop. Satoh, M. (2007) Global cloud-resolving model development and its seamless applications to weather & climate

researches. The third China-Korea-Japan joint conference on meteorology. Satoh, M. (2007) Global cloud-resolving model development and its seamless applications to weather & climate

researches. APCOM conference. (2008) NICAM. 6 HSS , 2008 3 .

6.3 Satoh, M., Nasuno, T., Miura, H., Tomita, H., Iga, S., Takayabu, Y. (2008) Precipitation statistics comparison

between global cloud resolving simulation with NICAM and TRMM PR data. High Resolution Numerical Modelling of the Atmosphere and Ocean, edited by Wataru Ohfuchi and Kevin Hamilton, 99-112.

7.

277-8568 5-1-5


－ 54 －－ 55 －

NICAM

Project name: Numerical Study of Cloud System Using NICAM 2007 April - 2008 March Project leader: Masaki SATOH, Center for Climate System Research, The University of Tokyo Project member: Wataru YANASE, Center for Climate System Research, The University of Tokyo Abstract:

Our goal is to understand various meso-scale cloud systems using NICAM, a global quasiuniform-grid atmospheric model. In particular, we are focusing on the genesis mechanism of tropical cyclones such as typhoons and hurricanes. Although it is generally difficult to simulate the genesis of tropical cyclones, our strategy is to deal with rare cases which can be predicted with less difficulty using the initial field more than three days prior to genesis. For this purpose, we conducted several simulations of cyclogenesis using NICAM with a 60-km grid spacing on the NIES super computer system. We started with five cyclogenesis cases of intense typhoons which occurred between 2004 and 2006, and found that we can simulate the genesis of typhoon 0621 using the initial field three days prior to genesis. We also found that the interaction of tropical easterly and westerly waves were associated with the cyclogenesis. Information about the predictability of cyclogenesis is useful for detailed study, including higher resolution simulations and sensitivity experiments. We expect that this study will promote the understanding of tropical cyclone genesis mechanisms. Keywords: Global cloud-resolving model, Tropical meteorology, Meso-scale meteorology, Tropical cyclone

－ 54 －－ 55 －


1998

199835.0 m 115 m3 1998

34.4 m1950

－ 56 －－ 57 －

8 21

1.

2. 2.1

CPU Total 189hrs 2.2

HSPF

3. 3.1

Su et al., 2005

, 2000; Xu et al., 2005 2 1998Wang et al., 2003 8

20098

2010 1998 2

1998

－ 56 －－ 57 －


3.2

445 km 294,911 km2 1 50 km

263,000 km2

31 15

20 1920 30 4955 km2

1998 2518 km2 70 49% Zhao et al., 2005; Zhang et al., 2006 1990

1 Liu, 1996

70

3.3

EPA Hydrological Simulation Program – FORTRAN HSPF Bicknell et al., 1997 1987 1988 2

Hayashi et al., 2004

HSPF HSPF2 Hayashi et al., 2008

1998Hayashi et al., 2008

HSPF

2

1

－ 58 －－ 59 －

Q1 Q2 Q3 (1)

Ch1: 3

21

12

21

131

21

121

21

11JJ

J hQb

hQaH

hQb

hQaH (2)

Ch2: 3

22

22

22

22JJ

J hQb

hQaHE (3)

Ch3: 3

23

32

23

333

23

323

23

33JJ

Jee h

QbhQaH

hQb

hQaH (4)

Q m3/s h m H m H=h Z Z (m) a, b

a=1/(2gB2) b=f /(16gB2) g 9.8m/s2 B m L m ff=8gn/h1/3 n

2 Q1 h1

HSPF-

19882 5 1

50 m 3.4 3.4.1 GRUs

GRU 5 1

2

－ 58 －－ 59 －


50 m 1 kmDEM 194

GRU

8 3.4.2 GRUs

194universal kriging

0.2524 1

National Centers for Environmental Prediction NCEP /National Center for Atmospheric Research NCAR Kalnay et al.,

1996 1

3.4.3 3(b)

, 1999 5 12,896 km2

2,785.4 km2 , 199950m - 1998 -

3(a) 30.0 m 89.4 m3 114 m3 35.0 m 278 m3 393 m3

7 9

3.4.4 1998

, 2004 2000 4( )

58,000-60,000 m3/s

(a) (b)

3 a 1998 Wang et al., 2003 b

－ 60 －－ 61 －

6 60,000 m3/s1998

3.4.5 3

1 1955 1966 41.31967 1972 34.7 1973 1996 27.8 1998 27.6%

Wang et al., 2005 1998 1950 19551966 1960 1967 1972

3.5

1998

, 2004; Hayashi et al., 2005

1998

3.5.1

134.40 m

4 19981998

35.36 m 38

34.75 m 24

4 1998

－ 60 －－ 61 －


196034.70 m 21

19504

5 6

19987

4

5 7 61998

7 81998 5

7 81950

7 1950

4

3.5.2 7 1950

60,000 m3/s1998 4,000

5,900 m3/s

6 19985 1998

－ 62 －－ 63 －

5

1998

Bicknell, B. R. et al. (1997) Hydrological Simulation Program--Fortran, User's Manual for Version 11.” Rep. No.

EPA/600/R-97/080, U.S. EPA, Athens, Ga. Hayashi, S. et al. (2004) HSPF simulation of runoff and sediment loads in the upper Changjiang River basin,

China, J. Environ. Eng., ASCE, 30 (7), 801-815. Hayashi, S. et al. (2005) Modeling of daily runoff in the Changjiang (Yangtze) River basin and its application to

evaluating the flood control effect of the Three Gorges Project, CGER`s Supercomputer Monograph Report Vol. 10, 69p.

Hayashi, S. et al. (2008) Daily runoff simulation by an integrated catchment model in the middle and lower regions of the Changjiang basin, China, J. Hydrol. Eng., 13(9), 846-862.

Kalnay, E. et al. (1996) The NCEP/NCAR 40-year reanalysis project, Bulletin of the American Meteorological Society, 77 (3), 437-471.

Liu, J. Y. (1996) Macro-scale survey and dynamic study of natural resources and environment of China by remote sensing. Chinese Science and Technology Publisher, Beijing, 353p.

Su B. et al. (2005) Trends in frequency of precipitation extremes in the Yangtze River basin, China: 1960-2003, Hydrological Sciences Journal, 50 (3), 479-492.

Wang, Q. et al. (2003) Using NOAA AVHRR data to assess flood damage in China, Environmental Monitoring and Assessment, 82, 119–148.

Wang, S. et al. (2005) Anastomosing river system along the subsiding middle Yangtze River basin southern China, Catena, 60, 147-163.

Xu, K. et al. (2005) Simulated sediment flux of 1998 big flood of Yangtze (Changjiang) River, China, Journal of Hydrology, 313, 221-233.

Zhao, S. et al. (2005) The 7-decade degradation of a large freshwater lake in central Yangtze River, China, Environ. Sci, Technol., 39, 431-436.

Zhang, J. et al. (2006) Measuring fluctuations in water storage in Lake Dongting, China, by Topex/Poseidon satellite altimetry, Environmental Monitoring and Assessment, 115(1-3), 23-37.

(1999) ‘98 , , , 185p.(2000) 2 , , 42(8)

31-43.

7 1998

－ 62 －－ 63 －


(2000) 1998 , ,, 200p.

(2004) 1998 , 12, 79-86.

4.

1998

2006

2007

2007

5.

GCMRCM

2

6. 6.1 Hayashi, S., Murakami, S., Xu, K-Q., Watanabe, M., Xu, B-H. (2008) Daily runoff simulation by an integrated

catchment model in the middle and lower regions of the Changjiang basin, China, J. Hydrol. Eng., 13(9), 846-862..

(2008) CIP-FEM 3, , 52, 1405-1410.

Dairaku, K., Emori, S., Higashi, H. (2008) Potential Changes in Extreme Events Under Global Climate Change, Journal of Disaster Research, 3(1), 39-50.

－ 64 －－ 65 －

(2007) , , 44, 555-561.

6.2

(2007) “ ”, , 51, 135-141.

6.3

(2007) , , 88-89.

(2007) , , , 9 .

7.

305-8506 16-2


－ 64 －－ 65 －


Project name: International Collaborative Research on Integrated Environmental Management in River Catchment 1996 April - 2010 March Project leader: Shogo MURAKAMI, National Institute for Environmental Studies Project members: Seiji HAYASHI, Hironori HIGASHI, Keiko NAKAJIMA, National Institute for Environmental Studies

Abstract:

In order to evaluate flood protection effects of the conversion of polders to retarding basins around Dongting Lake in the middle region of the Changjiang River, China, we applied the integrated watershed hydrological model using gauged daily precipitation data from 1998, when the second largest flood of last century occurred in the basin. Estimated storage capacity of Dongting Lake, in comparison with the 1998 flood period at an average water level of 35.0 m, increased 11.5×109 m3 after conversion of polders. However, the lake’s simulated daily average water levels showed that flood protection would have been impossible in the 1998 case when only increasing capacity in the confluence between the Changjiang mainstream and Dongting Lake. The model also indicated that flood protection was fully achieved at the confluence by making the volume diverging from the Changjiang mainstream to Dongting lake increase, using the diverging ratio of the 1950s under appropriate discharge control by the Three Gorges Dam. These results suggest that the “return land to lake” policy around Dongting Lake probably offers the best flood protection when the increased capacity of the lake is used for the control of water levels in the Jinjiang section of the Changjiang mainstream.

Keywords: Flood control, Water level, Changjiang River, Dongting Lake, Hydrologic model

－ 67 －

－ 67 －


GCMGCMGCM

Hayashi et al., 2007; , 2008

3AGCM5 Hayashi et al., 2005

Hayashi et al. 20050.1 50

wave-CISKAPE

－ 68 －－ 69 －

19 19

1.

GCMGCM

GCM, DCPAM Dennou-Club Planetary Atmosphere Model

2. 2.1

CPU Total 2,415hrs

2.2

AGCM5 SWAMP Project, 1998DCPAM

3. 3.1

Madden-Julian MJOGCM

APE Aqua Planet Experiment, http://www-pcmdi.llnl.gov/amip/ape/ 157 17 GCM

APE GCMAPE

－ 68 －－ 69 －


GCM Hayashi et al., 2005, 2007; , 2008 Hayashi et al. 2005 Kuo

Numaguti and Hayashi 1991 wave-CISK

1 KuoHayashi and Sumi, 1986; Numaguti and Hayashi, 1991

Hayashi et al. 2007 2008

3.2 3

AGCM5 T42L16

Hayashi et al. 2005, 2007 2008

wave-CISK Kuo Louis, 1979 Hayashi et al., 2005

Hayashi et al. 2005

0.1 50

3.3

1/10 10 1,

GCM

SST

wave-CISK

, 2008

－ 70 －－ 71 －

(a)

(b)

kg m-2 s-1 0.83

kg kg-1 0.55 K a Hayashi et al. 20050.1 b 10

－ 70 －－ 71 －


3.4 APE

2007 11 APE

wave-CISK APE SSTAPE

wave-CISK

Aqua-Planet Experiment Project: http://www-pcmdi.llnl.gov/projects/amip/ape/ Hayashi, Y.-Y., Odaka, M., Yamada, Y., Morikawa, Y., Ishiwatari, M., Nakajima, K., Takehiro, S. (2005) An

aqua-planet experiment on structurization of equatorial precipitation activity and related software development toward an atmospheric general circulation model for terrestrial planets. CGER’s Supercomputer Activity Report, National Institute for Environmental Studies, Vol. 12-2003, 77-86.

Hayashi, Y.-Y., Ishiwatari, M., Yamada, Y., Morikawa, Y., Takahashi, Y. O., Nakajima, K., Odaka, M., Takehiro, S. (2007) Equatorial Precipitation Patterns in Aqua-Planet Experiments: Effects of Vertical Turbulent Mixing Processes. CGER's Supercomputer Activity Report, National Institute for Environmental Studies, Vol. 14-2005, 69-76.

Hayashi, Y.-Y., Sumi, A. (1986) The 30-40 day oscillations simulated in an ''aqua planet'' model. J. Meteor. Soc. Japan, 64, 451-467.

(2008) . 18 , 65-72.

Louis, J.-F. (1979) A parametric model of vertical eddy fluxes in the atmosphere. Bound. Layer Meteor., 17, 187-202.

Numaguti, A., Hayashi, Y.-Y. (1991) Behavior of cumulus activity and the structures of circulations in an ''aqua planet'' model. Part I. The structure of the super clusters. J. Met. Soc. Japan, 69, 541-561.

SWAMP Project (1998) AGCM5. http://www.gfd-dennou.org/arch/agcm5/, GFD Dennou Club. 4.

wave-CISK

2007 11 APE APE

5.

DCPAMDCPAM

－ 72 －－ 73 －

6. 6.1 Ishiwatari, M., Nakajima, K., Takehiro, S., Hayashi, Y.-Y. (2007) Dependence of climate states of gray

atmosphere on solar constant: from the runaway greenhouse to the snowball states. J. Geophys. Res., 112, D13120, doi:10.1029/2006JD007368.

6.2

(2007) RDoc . , 54, 185-190.

6.3

(2007) . 2007 , 2007 05 .

(2007) :

. 2007 , 2007 05 . (2007)

: . 2007 2007 05.

(2007) . 2007 , 2007 05 .

(2007) . 40 , 2007 7 .

(2007) . .

2007, 2007 8 . (2007)

. 2007 , 200710 .

(2007) . 2007 , 2007 9 .

Nakajima, K., Yamada, Y., Takahashi, Y. O., Ishiwatari, M., Takaya,K., Ohfuchi, W., Hayashi, Y.-Y. (2007) On the varieties of tropical precipitation patterns forced by an SST anomaly on the equator:some expectations and results, APE Workshop 2007, November 2007.

Hayashi, Y.-Y., Yamada, Y., Takahashi Y. O., Ishiwatari, M., Nakajima,K., Ohfuchi, W., GFD Dennou Club (2007) On the varieties of spontaneously generated tropical precipitation patterns, APE Workshop 2007, November 2007.

6.4

DCPAM: GFD Dennou Club Planetary Atmospheric Model. http://www.gfd-dennou.org/library/dcpam/

. APE Project: GFD Dennou Club APE project. http://www.gfd-dennou.org/library/ape/ . 7.

657-8501 1-1


－ 72 －－ 73 －


Project name: A Study on the Variety of the Representations of Equatorial Precipitation Activities 2007 April - 2008 March Project leader: Yoshi-Yuki HAYASHI, Graduate School of Science, Kobe University Project members: Masaki ISHIWATARI, Yasuhiro MORIKAWA, Graduate School of Science, Hokkaido University Yukiko YAMADA, National Institute for Environmental Studies Yoshiyuki TAKAHASHI, Graduate School of Science, Kobe University Abstract:

The purpose of this study is to understand varieties of behaviors of tropical precipitation activities represented by atmospheric general circulation model (GCM) through aqua-planet experiments with simplified physical processes. In past years, in order to investigate the effect of vertical diffusion process on model representations of eastward propagating precipitation activities, we have performed experiments with fixed vertical profiles of diffusion coefficients which are independent of atmospheric stability and vertical shear (Hayashi et al., 2007, 2008). In our previous experiments, all the magnitudes of diffusion coefficients of water vapor, temperature, and momentum were changed simultaneously. Due to this configuration, we were not able to exclude the effect of the change of frictional convergence caused by the change of momentum diffusion coefficients on behaviors of eastward propagating precipitation activities. This year, aiming for evaluating the effect of vertical diffusion of water vapor on number and horizontal scale of eastward propagating precipitation activities, we performed experiments with various magnitudes of water vapor diffusion coefficients but fixed diffusion coefficients of temperature and momentum.

The model used here is GFD Dennou Club AGCM5.3, a three-dimensional primitive model which includes simple hydrological and radiation processes (Hayashi et al., 2005). The entire surface is covered with the ocean (aqua-planet configuration) with a fixed value of sea surface temperature (SST). The distribution of SST is equatorially symmetric, and zonally uniform. In the vertical diffusion process, we use diffusion coefficient profiles which are produced artificially with reference to the results of Hayashi et al. (2005). The magnitude of diffusion coefficients of water vapor are changed from 0.1 times to 50 times the reference profile, while those of temperature and momentum are fixed.

The results show that the westward propagating precipitation activities weaken with the increase of the magnitude of vertical diffusion coefficient for water vapor. The eastward propagating precipitation activities do not show clear dependence on the magnitude of vertical diffusion coefficients for water vapor.. We could not identify the process which determines the number of eastward propagating precipitation activities. We submitted our understandings on the variety of precipitation activities obtained so far from the viewpoint of wave-CISK dynamics and moisture transport to APE (aqua-planet experiment project), contributing in considering the variety of tropical precipitation activities appearing in the various climate models. Keywords: General circulation model, Aqua planet experiments, Tropical precipitation pattern, Vertical turbulent mixing

－ 75 －

－ 75 －


3

3 Navier-StokesLarge Eddy Simulation LES Detached Eddy Simulation DES

22

3 1

”Case A” 4”Case B” ”Case B”

”end-effect”2

”Case A”

”end-effect”

－ 76 －－ 77 －

3

3

12 19

1.

2

2. 2.1

CPU Total 0hr

2.2 2006 CASL Contour Advective Semi Lagrangian

2007 CASL

20072007 2007

2008

3. 3.1

3 Navier-StokesLarge Eddy Simulation LES Detached Eddy Simulation DES

3.2

20 2 Euler 2

Onsager 1949 ; Joyce and

－ 76 －－ 77 －


Montgomery 1973 ; Kida 1975 ; Lundgren and Pointin 1997Yatsuyanagi et al. 2005 2

N = 67243

1 Pedlosky, 1979 McWilliams 1984, 1990

Meacham et al. 1997Miyazaki et al. 2001

Meachamcounter-rotationg

/2Dritschel et al. 2004

Li et al. 2006N wire 2N 3N

3

3.3 3.3.1

2 vu,

yu ,

xv . 1

0qyxxyt

. 2

q

2

2

2

2

2

2

zyxq 3

3 iR

iˆ

)(ˆ1

i

N

iiq Rr 4

N 3.3.2 N Hamiltonian H 2/)1(NN

N

jimijHH

),(,

ji

jimijH

RR4

ˆˆ. 5

－ 78 －－ 79 －

3

mijH ),,( iiii ZYXR , ),,( jjji ZYXR 2

iˆ , j

ˆ i

ii

i

YH

tX

ˆ1

dd

, ii

i

XH

tY

ˆ1

dd

. 6

Hamiltonian H P, Q , I4

N

ii

N

iii XP

11

ˆˆ , N

ii

N

iiiYQ

11

ˆˆ , 7

N

ii

N

iiii YXI

11

22 ˆ)(ˆ . 8

t Poisson HIQP ,,22 3 Liouville-Arnol’d

4

3.4

2.4323 N = 2000 1ˆ,...,2,1 Ni

”Case A” ELundgren and Pointin, 1997 t

106

E = Ec r

z F r, z t = 10 ~ 20 t = 201 ”end-effect”

”Case A”

1 F r, z |z|

”Case A” 4 ”Case B”

2 ”Case A” ”end-effect” 2

－ 78 －－ 79 －


2 4 Case B

”Case A” ”Case C” ”Case D”3 4

r2 0.5, r1 0 ”Case C””Case A” ”Case D” ”Case A”

”end-effect”

3 Case C, Case D

4 Case C, Case D

－ 80 －－ 81 －

3

”Patch Model” a z0 E = Ec

”Patch Model” 5”end-effect”

5 ”Patch Model”

Dritschel, D. G., Reinaud, J. N., McKiver, W. J. (2004) The quasi-geostrophic ellipsoidal vortex model. J. Fluid Mech., 505, 201-223.

Joyce, G., Montgomery, D. (1973) Negative temperature states for the two-dimensional guiding center plasma. J. Plasma Phys., 10 , 107-121.

Kida, S.(1975) Statistics of the System of Line Vortices. J. Phys. Soc. Jpn., 39(5) , 1395-1404. Li, Y., Taita, H., Takahashi, N., Miyazaki, T. (2006) Refinements on the Quasi-geostrophic Ellipsoidal Vortex

Model. Phys. Fluids 18 (7) 076604 1-8. Lundgren, T. S., Pointin, Y. B. (1997) Statistical Mechanics of Two-Dimensional Vortices. J. Stat. Phys., 17(5) ,

323-355. McWilliams, J. C. (1984) The emergence of isolated coherent vortices in turbulent flow.J. Fluid Mech., 146,

21-43. McWilliams, J. C. (1990) The vortices of two-dimensional turbulence. J. Fluid Mech., 219, 361-385. Meacham, S. P., Morrison, P. J., Flierl, G. R. (1997) Hamiltonian Moment Reduction for Describing Vortices in

Shear. Phys. Fluids, 9 , 2310-2328. Miyazaki, T., Furuichi, Y., Takahashi, (2001) N.Quasigeostrophic Ellipsoidal Vortex Model. J. Phys. Soc. Jpn.,

70(7), 1942-1953. Onsager, L. (1949) Statistical hydrodynamics, Nuovo Cimento Suppl., 6, 279-287. Pedlosky, J. (1979) Geophysical Fluid Dynamics. Splinger, New York, 624. Yatsuyanagi, Y., Kiwamoto. Y., Tomita. H., Sano. M. M., Yoshida. T., Ebisuzaki. T. (2005) Dynamics of

Two-Sign Point Vortices in Positive and Negative Temperature States. Phys. Rev. Lett., 94, 054502.

－ 80 －－ 81 －


4.

4 ”end-effect”

”end-effect” ”Patch Model”

5.

6. 6.1

(2008) , ( ), 27(1), 51 63. Hoshi, S., Miyazaki, T. (2008) Statistics of Quasi-geostrophic Point Vortices. Fluid Dynamics Research 40,

662-678. 6.2 Hoshi, S., Li, Y., Takahashi, N., Miyazaki, T. (2007) Statistical Mechanics of Quasi-geostrophic Mono- and

Poly-disperse Point Vortex Systems. The Fifth International Conference on Fluid Mechanics. 7.

182-8585 1-5-1


－ 82 －－ 83 －

3

Project name: Order Vortex Structures and Three-Dimensional Scalar Transport in Geophysical Flows

2000 April - 2008 March

Project leader: Takeshi MIYAZAKI, The University of Electro-Communications

Project member: Yingtai LI, The University of Electro-Communications

Abstract: There are many long-lived vortex structures in geophysical fluid movement, such as the polar vortex

(which causes ozone hole) and mesoscale ocean vortexes. These rule not only the momentum and energy but also transport and mixture processes of material. These transport phenomena should be captured accurately in order to forecast the geophysical environment. Rapid increases in computing ability will make the Navier-Stokes three-dimensional global environmental analysis possible. Future global environmental forecasting will surely be able to utilize numerical operations similar to the large-scale turbulent flow models already in use in the field of engineering (such as Large Eddy Simulation (LES) and Detached Eddy Simulation (DES)). Before this becomes possible, it is necessary to clarify the physical mechanism of vortex structures.

Geophysical flows are under the strong influence of the buoyancy force associated with stable density stratification and the Coriolis force of the earth’s rotation. Vertical motions are suppressed because of the effects of the Coriolis force and stable stratification. At the lowest order of approximation, geophysical flows are considered to be two-dimensional. There have been many theoretical studies on a two-dimensional point vortex system. The next order of approximation is ‘quasi-geostrophic approximation’, which incorporates the three-dimensionality of the geophysical flow field. Under quasi-geostrophic approximation, coherent vortices dominate the dynamics.

In this paper, we investigate the statistical properties of quasi-geostrophic point vortices both theoretically and numerically. The most probable distributions are determined based on the maximum entropy theory. We investigate the statistics of the equilibrium state, which is obtained by averaging the numerical data. We compute numerically the time evolution of point vortices located randomly in a rectangular box initially. The radial distribution near the lids is concentrated more tightly for the ‘rectangular case’ than in the ‘cubic case’. The end effect is sharper in this case and will become even sharper for higher boxes, where the distribution will consist of the central two-dimensional distribution and those of the thin upper and lower lid regions. Next, we investigate the distribution of the higher and lower energy case. The obtained numerical results are in good qualitative agreement with theoretical predictions based on the maximum entropy theory. The value for the energy constraint increases if the distribution is concentrated more closely around the axis of symmetry. The angular momentum is determined by a simple summation of the value on each horizontal plane, whereas the energy is determined by the whole three-dimensional distribution. The end-effect appears as a delicate balance between these competing effects. The distribution in the center region expands radially for lower energy and shrinks for higher energy. In order to keep the angular momentum unchanged, the distribution near the lids should shrink for lower energy and should expand for higher energy.

Keywords: Quasi-geostrophic, Maximum entropy theory, Scalar transport

－ 82 －－ 83 －


3DNS

－ 84 －－ 85 －

15 19

1.

2.

2.1CPU Total 51,545hrs

2.23

DNS 6 DNS

3.

3.1DNS

3.2

－ 84 －－ 85 －


, 2004

Komori et al., 1993 and 1996

Angelis et al., 1997; Nakagawa and Hanratty, 2001; , 2003; Zilker et al., 1977 DNS

3.3

Navier-StokesMAC Marker And Cell

1

Run 1 0° Run 227°, 48°, 70° Run 3, 4, 5

90° Run 6 6

3.4

2 DF,w DP,wDF,f

3 DF,w

jj

i

ij

ij

i

i

i

xxu

xp

xu

utuxu

21

0

－ 86 －－ 87 －

Angelis, V. D., Lombardi, P., Banerjee, S. (1997) Direct numerical simulation of turbulent flow over a wavy

wall. Phys. Fluids A, 9, 2429-2442. Komori, S., Nagaosa, R., Murakami, Y., Chiba, S., Ishii, K., Kuwahara, K. (1993) Direct numerical simulation

of three-dimensional open-channel flow with zero-shear gas-liquid interface. Phys. Fluids A, 5, 115-125. Komori, S. (1996) Turbulence structure and CO2 transfer at the air-sea interface and turbulent diffusion in

thermally-stratified flows. CGER's Supercomputer Monograph Report, 1, Centre for Global Environmental Research, National Institute for Environmental Studies, Environment Agency of Japan.

3

a b c

2

d e f

1 (a) Run 1, (b) Run 2, (c) Run 3, (d) Run 4, (e) Run 5, (f) Run 6.

－ 86 －－ 87 －


Nakagawa, S., Hanratty, T. J. (2001) Particle image velocimetry measurements of flow over a wavy wall. Phys. Fluids A, 13, 3504-3507.

(2003) . , 6, 839-846. (2004) . (B ), 70, 644-649.

Zilker, D. P., Cook, G. W., Hanratty, T. J. (1977) Influence of the amplitude of a solid wavy wall on a turbulent flow. Part1. Non-separated flows. J. Fluid Mech., 82, 29-51.

4.

DNS

5.

6. 6.1

(2007) . B , 73, 1518-1524.

Imashiro, T., Yamamoto, T., Kurose, R., Komori, S. (2007) The effects of swells on turbulence structure over wavy walls. In Proc. of 5th International Symposium Turbulence and Shear Flow Phenomena (ISTFP), 3, 1281-1286.

6.2 (2007) .

2007, 2007 11 17 18 ( ). 7.

606-8501Tel: 075-753-5244 Fax: 075-753-5245 E-mail: [email protected]

－ 88 －－ 89 －

Project name: Mass Transfer Mechanism at and Below the Air-Water Interface in the Ocean and the Effects of Swell on the Mass Transfer at the Air-Sea Interface 2003 April - 2008 March Project leader: Satoru KOMORI, Kyoto University Project member: Ryoichi KUROSE, Takenori IMASHIRO, Kyoto University Abstract:

Global warming, which has become one of the most serious environmental problems in recent decades, is known to be caused by emissions of greenhouse gasses such as carbon dioxide (CO2) and methane (CH4). In order to predict the increase of atmospheric temperature, it is of great importance to precisely estimate the global carbon cycle. One of the important issues is to precisely predict mass transfer velocity of greenhouse gases across the air–sea interface between atmosphere and oceans. Generally, there exist two types of waves in oceans: wind waves generated by only wind shear acting on the air–sea interface, and swells propagated from afar with low frequency. The purpose of this study is to apply three-dimensional direct numerical simulations (DNS) to the turbulent air boundary layer over a wavy wall, which imitates the air–water interface consisting of both wind waves and swells, and investigate the effects of the swells with various directions on the turbulence structure and drag over/on the wavy wall. The results show that parallel swell increases the turbulence intensity and the Reynolds stress over the wavy wall. The swell also increases the pressure drag and decreases the friction drag on the wavy wall, and consequently increases the total drag because of remarkable increase of pressure drag. As the inclination angle of the swell against the wind increases from parallel to perpendicular, the swell effect on the drag becomes weak and finally vanishes. The reduction of friction drag due to swell suggests that the mass transfer velocity across the wind-driven wavy air–water interface is suppressed due to swell. Keywords: Mass transfer, Air-water interface, Ocean, Wind wave, Swell, Wavy wall

－ 88 －－ 89 －


Batchelor

BatchelorBatchelor

－ 90 －－ 91 －

19 19

1.

100differential

diffusion

2. 2.1

CPU Total 6,694hrs

2.2 x, y, z 3

2563 5123

6 600

Pr Pr=1 6

3. 3.1

Batchelor Batchelor, 1956

192 1 3

－ 90 －－ 91 －


BatchelorBatchelor

3.2

100Gargett et al., 2003

Reb / N 2

Reb O(103 )Jackson and Rehmann, 2003KSalt KHeat 0.1 0.8

Jackson et al., 2005differential diffusion KSalt KHeat

Nash and Moum, 2002; Gargett, 2003differential diffusion

3.3

3 2563 5123

3 2

3.4

1

－ 92 －－ 93 －

1 k KEvort kKEwave k

ES k Pr=6 ET kPr=1

(a) (b)

2 k1 2a k3 2b ET

Pr=1 ES Pr=6a

ES ET

Batchelor b

2Pr=6

Batchelor 2 a

－ 92 －－ 93 －


2 bBatchelor

3 Pr=63b Pr=1

3aBatchelor

(a) (b)

3 x 2 aPr=1 b Pr=6

(a) (b)

4 z 2 a

Pr=1 b Pr=6

z 4 Pr=1a Pr=6 4b

Batchelor

－ 94 －－ 95 －

Batchelor, G. K. (1956) Small-scale variation of convected quantities like temperature in turbulent fluid. Part 1. General discussion and the case of small conductivity. J. Fluid Mech., 5, 113-133.

Gargett, A. E. (2003) Differential diffusion: an oceanographic primer. Prog. Oceanogr., 56, 559-570. Gargett, A. E., Merryfield, W. J., Holloway, G. (2003) Direct numerical simulation of differential scalar

diffusion in three-dimensional stratified turbulence. J. Phys. Oceanogr., 33, 1758-1782. Jackson, P. R., Rehmann, C. R. (2003) Laboratory measurements of differential diffusion in a diffusively stable,

turbulent flow. J. Phys. Oceanogr., 33, 1592-1603. Jackson, P. R., Rehmann, C. R., Saenz, J. A., Hanazaki, H. (2005) Rapid distortion theory for differential

diffusion. Geophysical Research Letters, 32, L10601-10604. Nash, J. D., Moum, J. N. (2002) Microstructure estimates of turbulent salinity flux and the dissipation spectrum

of salinity. J. Phys. Oceanogr., 32, 2312-2333.

4.

50Batchelor

5.

6. 6.1 Hanazaki, H. (2008) Slowly oscillating modes in the passive scalar diffusion in stratified turbulence. Physics of

Fluids 20, 055106 (13 pages). Hanazaki, H., Konishi, K. (2008), Schmidt number effects on the flow past a sphere moving vertically in a

stratified diffusive fluid. Physics of Fluids (accepted).Hanazaki, H. (2008) Effects of the slow modes in the differential diffusion in stratified sheared turbulence. Proc.

IUTAM Symposium on Computational Physics and New Perspectives in Turbulence. pp. 397-401 Springer. 6.2 Hanazaki, H., Miyao, T. (2007) Absence of small-scale fluctuations of high-Pr buoyant scalars in stratified

turbulence. 60th Annual Meeting of the American Physical Society Division of Fluid Dynamics. Bulletin of the American Physical Society, 52 (17), pp. 65.

6.3 Hanazaki, H., Konishi, K. (2007) Differential diffusion in double-diffusive stratified turbulence. The 11th

European Turbulence Conference. (Porto, Portugal, 2007).

－ 94 －－ 95 －


Hanazaki, H., Konishi, K., Miyao, T. (2008) Absence of small-scale fluctuations of high-Prandtl number scalars in stratified turbulence. 22nd International Congress of Theoretical and Applied Mechanics (Adelaide, Australia, 2008).

7.

606-8501


－ 96 －－ 97 －

Project name: The Modeling and Prediction of Eddy Diffusion Coefficient of Heat and Salt in the Ocean by the Numerical Simulation of Turbulence 2007 April - 2008 March Project leader: Hideshi HANAZAKI, Kyoto University Abstract:

Ocean circulation, also known as thermohaline circulation, is generated by the buoyancy effects of salt and heat. In most numerical models of ocean circulation, the same turbulent diffusion coefficient is used both for heat and salt. However, it has recently been discussed that there would be a difference between the turbulent diffusion coefficients due to the difference in the molecular diffusion. In this study, structures of heat and salinity distributions are analyzed across a small diffusion scale called Batchelor scale, and their effects on the practically important macro quantities, like eddy diffusion coefficients (fluxes of heat and salt), are investigated. The results show that, in the vertical spectrum routinely observed in the ocean, there are some differences between heat and salt in agreement with the prediction by Batchelor which states that scalars with smaller molecular diffusivities have smaller structures. On the other hand, the horizontal spectrum of heat and salt agrees almost completely, in contradiction to the prediction. These results suggest that in oceanic observation, the inapplicability of Batchelor’s scaling might well be overlooked even if it actually exists. Keywords: Stratified turbulence, Double-diffusion of heat and salt

－ 96 －－ 97 －


CAI

Nick Schutgens

GOSAT CAI

SPRINTARS CCSR/NIES/FRCGC-MIROC CAI

AERONET SKYNET MODIS MIDORI-II/GLI

40 5

CAI

SPRINTARS

GOSAT

－ 98 －－ 99 －

CAI

CAI

19 19

Nick Schutgens 1.

GOSATCAI

CAI

GOSAT 2. 2.1


SPRINTARS CCSR/NIES/FRCGC-MIROC AERONET

SKYNETMODIS MIDORI-II/GLI AOT

AOTEKFCAI

3. 3.1

SPRINTARS CCSR/NIES/FRCGC-MIROC AERONET

SKYNET MODIS MIDORI-II/GLI

EKFSPRINTARS

3.2

2008 / / GOSAT

－ 98 －－ 99 －


GOSAT CAI

CAI

CAI

3.3

CCSR/NIES/FRCGC-MIROCSPRINTARS EKF

AERONET SKYNETSPRINTARS

SPRINTARS

3.4

SPRINTARSSX-8R

SPRINTARS MIROC AGCMSPRINTARS

1 SKYNETAOT

UNEP/ABC/EAREX05 2005 4Nakajima et al., 2007 1 a

SKYNET 1 b

EKF AERONET 200

SPRINTARS 500 nm AOT500Local Ensemble Transform Kalman Filter LETKF Hunt et al., 2007;

Miyoshi and Yamane, 2007 2AERONET

40 5NIES/GOSAT

CCN

AGCM Lohmann and Feither, 2005

CCNGhan et al. 1993

AGCM

－ 100 －－ 101 －

CAI

Takemura et al., 2005

s-Pa Abdul-Razzak et al., 1998 m-PaAbdul-Razzak and Ghan, 2000 m-Pa

CDR AGCMNCAP 2003

6 3 s-Pa m-Pa CDR 2003 10

m-Pa CDR

CDR

CDRCDR

1 500 nm

a b

(a)

(b)

－ 100 －－ 101 －


2 LETKF SPRINTARS 500 nm ac b 10

(a)

(b)

(c)

－ 102 －－ 103 －

CAI

3 SPRINTARS 2003 10 m-Paa s-Pa b

Abdul-Razzak, H., Ghan, S. J., Rivera-Carpio, C. (1998) A parameterization of aerosol activation 1. Single aerosol types. J. Geophys. Res., 103, D6, 6123-6131.

Abdul-Razzak, H., Ghan, S. J. (2000) A parameterization of aerosol activation 2. Multiple aerosol types. J. Geophys. Res., 105, D5, 6,837-6,844.

Ghan, S. J., Chuang, C. C., Penner, J. E. (1993) A parameterization of cloud droplet nucleation part I. single aerosol type. Atmos. Res., 30,197-30,221.

Hunt, B. R., Kostelich, E. J., Szunyogh, I. (2007) Efficient data assimilation for spatiotemporal chaos. A local ensemble transform Kalman filter. Physica D-Nonlinear Phenomena, 230, 1-2, 112-126.

Lohmann, U., Feither, J. (2005) Global indirect aerosol effects: a review. Atmos. Chem. Phys., 5, 715-737. Miyoshi, T., Yamane, S. (2007) Local ensemble transform Kalman filtering with and AGCM at a t159/L48 res-

olution. Monthly weather Review, 135, 11, 3841-3861. Nakajima, T., Yoon, S.-C., Ramanathan, V., Shi, G.-Y., Takemura, T., Higurashi, A., Takamura, T., Aoki, K.,

Sohn, B.-J., Kim, S.-W., Tsuruta1, H., Sugimoto, N., Shimizu, A., Tanimoto, H., Sawa, Y., Lin, N.-H., Lee, C.-T., Goto, D., Schutgens1, N. (2007) Overview of the Atmospheric Brown Cloud East Asian Regional Experiment 2005 and a study of the aerosol direct radiative forcing in east Asia. J. Geophys. Res., 112, D24S91, doi:10.1029/2007JD009009.

Takemura, T., Nozawa, T., Emori, S., Nakajima, T.Y., Nakajima, T. (2005) Simulation of climate response to aerosol direct and indirect effects with aerosol transport-radiation model. J. Geophys. Res., doi:10.1029/2004JD005029.

4.

(a) (b)

－ 102 －－ 103 －


5.

6. 6.1 Goto, D., Takemura, T., Nakajima, T. (2008) Importance of global aerosol modeling including secondary organ-

ic aerosol formed from monoterpene. J. Geophys. Res., 113, D07205, doi:10.1029/2007JD009019. Mukai, M., Nakajima, T. Takemura, T. (2008) A study of anthropogenic impacts of the radiation budget and the

cloud field in East Asia based on model simulations with GCM. J. Geophys. Res., 113, D12211, doi:10.1029/2007JD009325.

Nakajima, T., Yoon, S.-C., Ramanathan, V., Shi, G.-Y., Takemura, T., Higurashi, A., Takamura, T., Aoki, K., Sohn, B.-J., Kim, S.-W., Tsuruta, H., Sugimoto, N., Shimizu, A., Tanimoto, H., Sawa, Y., Lin, N.-H., Lee, C.-T., Goto, D., Schutgens, N. (2007) Overview of the Atmospheric Brown Cloud East Asian Regional Experiment 2005 and a study of the aerosol direct radiative forcing in east Asia. J. Geophys. Res., 112, D24S91, doi:10.1029/2007JD009009.

6.2

(2007) .2007 , , 19 5 .

(2007) .2007 , , 19 5 .

Goto, D., Takemura, T., Nakajima T. (2007) Impact of aerosol competition effects on global cloud field using a general circulation model. IUGG2007, Perugia, Italy, July 2007.

(2007) GCM . 2007 , , 19 10 .

7.

277-8568 5-1-5

Tel. 04-7136-4370 Fax. 04-7136-4375 e-mail: [email protected]

－ 104 －－ 105 －

CAI

Project name: Development of a Combined System for CAI-Satellite Imager Analysis and Model Si-mulation


Project leader: Teruyuki NAKAJIMA, Center for Climate System Research, The University of Tokyo Project members: Nick SCHUTGENS, Makiko MUKAI, Daisuke GOTO, Center for Climate System Research, The Univer-sity of Tokyo

Abstract:

To obtain a first guess of the aerosol load in the atmosphere for retrieval by the cloud-aerosol imager (CAI) on board the GOSAT satellite and to substitute invalid or missing satellite data with simulated data, we propose to combine simulated data from a global three-dimensional aerosol transport-radiation model (SPRINTARS) coupled to the CCSR/NIES/FRCGC-GCM (MIROC) with measured data by CAI. We compared simulated aerosol distributions by SPRINTARS with observations by AERONET and SKYNET surface networks and also by MODIS and MIDORI-II/GLI satellite-borne imagers. These comparisons show that emission inventories and radii of aerosols in SPRINTARS should be modified. We also devel-oped and are testing an assimilation system for aerosols using an Ensemble Kalman Filter for SPRINTARS. In numerical experiments with 40 ensemble members, for example, we can get AOD values close to real values after an initial period of five days. Next year, we hope to optimize the assimulation system and test it for a variety of simulations.

We also examined how aerosol information from CAI can be useful to climate change studies by esti-mating changes in cloud and precipitation fields due to aerosols. For this purpose, we developed new aero-sol-cloud interaction processes for SPRINTARS, especially aerosol activation processes. We find that it is important to treat aerosol competition effects between smaller and larger aerosols, when aerosols act as cloud condensation nuclei (CCN). This means that aerosol size distributions are critical for estimating cli-mate change due to aerosols and should ideally be estimated by assimilation with high confidence. In the next year, we want to examine aerosol effects on cloud and precipitation fields for improving SPRINTARS.

Keywords: GOSAT, Carbon dioxide, Aerosol

－ 104 －－ 105 －


GOSAT

GOSAT 2008

GOSAT DHF GOSAT Data Handling Facility GOSAT GOSAT DHF

3

19

GOSAT DHF GOSAT3

GOSAT

－ 106 －－ 107 －

GOSAT

GOSAT

19 21

1.

Greenhouse gases Observing SATellite; GOSAT 20GOSAT

2.219

GOSAT 2. 2.1

CPU Total 0hr

2.2 19

GOSATGOSAT Data Handling Facility; GOSAT DHF

GOSAT 3

3.

3.1

GOSAT CO2 CH4

GOSAT DHFGOSAT JAXA/EORC 1

1

3

GOSAT DHF

－ 106 －－ 107 －


GOSAT DHF

1 GOSAT DHF

3.2

GOSAT20

GOSATkm

3.3 GOSAT

2 GOSAT2 3 4 3 2

TANSO-FTS CO2

CH4 TANSO-CAI3 3 3

1 24 2

3 2 1

2 2 42 4

－ 108 －－ 109 －

GOSAT

3 SPRINTARS Spectral Radiation-Transport Model for Aerosol Species

SPRINTARS Takemura et al. 2000SWIR TIR

2 20

Maksyutov and Inoue, 2000 FTSSWIR TIR CO2 CH4

SWIR TIR

CO2 64

4CO2 CH4

L2L2

L3L3 L4L4

L1BL1B

2

1

1

1

L3L3

2008/06/17

FTS

CAITIR2 m

1

2

:

GOSAT1 : NIES2 :

GOSAT/DHF

:

2 GOSAT

3.4 2007 1 GOSAT DHF

－ 108 －－ 109 －


19GOSAT DHF

20

3

Maksyutov, S., Inoue, G. (2000) Vertical profiles of random and CO2 simulated by the global atmospheric

transport model. CGER’s supercomputer activity report, vol.7-1998, CGER-I039-2000, 39-41. Tsukuba, Japan: CGER NIES.

Takemura, T., Okamoto, H., Maruyama, Y., Numaguti, A., Higurashi, A., Nakajima, T. (2000) Global three-dimensional simulation of aerosol optical thickness distribution of various origins, J. Geophys. Res., 105, 17853-17873.

4.

GOSAT2008 GOSAT GOSAT DHF GOSAT

2 4

5. GOSAT 3

6. 6.1

(2008) GOSAT. , 28(2), 127-132.

Aoki, T., Yokota, T., Nobuta, K., Kotani, A. (2008) The correction of disturbed near infrared spectra to be observed by space-borne Fourier Transform Spectrometer of GOSAT. , 28(2), 143-151.

(2008) . ,

28(2), 152-160. Maksyutov, S., Kadygrov, N., Nakatsuka, Y., Patra, P. K., Nakazawa, T., Yokota, T., Inoue, G. (2008) Projected

impact of the GOSAT observations on regional CO2 flux estimations as a function of total retrieval error. , 28(2), 190-197.

6.2 Maksyutov, S., Nakatsuka, Y., Belikov, D., Valsala, V. (2008) Atmospheric CO2 simulation with optimized

surface flux climatology for use in GOSAT CO2 retrieval. EGU General Assembly 2008. EGU2008-A- 00541.

Yokota, T., Watanabe, H., Ishihara, H., Matsunaga, T., Uchino, O., Morino, I., Takahashi, F. (2008) Outline of the data processing of carbon dioxide and methane and the data policy of the Greenhouse gases Observing Satellite (GOSAT). EGU General Assembly 2008. EGU2008-A- 07988.

(2008) GOSAT. 2008 . 194.

(2008) GOSAT/FTS . ( ) 44 . 87-88.

－ 110 －－ 111 －

GOSAT

(2008) GOSAT TANSO-FTS-SWIR ( 1 2) . ( )

44 . 89-90. (2008) GOSAT

. ( ) 44. 97-98.

Uchino, O., Morino, I., Araki, M., Yokota, T. (2008) Validation Plan of GOSAT Standard Products. 5th International Workshop on Greenhouse Gas Measurements from Space.

Yokota, T., Aoki, T., Bril, A., Eguchi, N., Morino, I., Oshchepkov, S., Ota, Y., Yoshida, Y. (2008) Overview of the GOSAT Project Status-Progress of Algorithm Development. 5th International Workshop on Greenhouse Gas Measurements from Space.

Maksyutov, S., Eguchi, N., Nakatsuka, Y., Saito, R., Belikov, D., Shirai, T., Patra, P.K. (2008) Analysing atomospheric CO2/CH4 variability to derive error covariance matirixes for retrievals. 5th International Workshop on Greenhouse Gas Measurements from Space.

Watanabe, H., Ishihara, H., Kawazoe, F., Hayashi, K., Yokota, T., Matsunaga, T., Hiraki, K. (2008) GOSAT Data Products processed at NIES GOSAT DHF and Research Annoucement. 5th International Workshop on Greenhouse Gas Measurements from Space.

7.

305-8506 16-2


－ 110 －－ 111 －


Project name: Developing, Maintaining and Operating Systems to Process Observational Data from the Greenhouse Gases Observing SATellite (GOSAT)

Project leader: Hiroshi WATANABE, National Institute for Environmental Studies Project members: Tatsuya YOKOTA, Tsuneo MATSUNAGA, Kaduo HIRAKI, Hironari ISHIHARA, Koji NOBUTA, Yasuhiro YOSHIDA, Emi OTA, Nobuhiro KIKUCHI, Tadayoshi MURAKAMI, Takuma NIHIRA, Hiroyuki KOBAYASHI, Fumiyoshi AIKAWA, National Institute for Environmental Studies Abstract:

The Greenhouse Gases Observing SATellite (GOSAT) is scheduled to be launched in early 2009. The National Institute for Environmental Studies (NIES) is in charge of data processing algorithm development, higher-level processing, validation, distribution of data products to external parties, and estimation of carbon flux using atmospheric tracer transport models. The GOSAT Data Handling Facility (DHF) is being developed for achieving these purposes. The following three computer facilities will be used for GOSAT data processing: 1) GOSAT DHF 2) NIES supercomputer 3) an external computer center outside of NIES. Aerosol transport model simulation, atmospheric transport model simulation, CO2 and CH4 inverse model calculation will be executed using the NIES supercomputer. The NIES supercomputer underwent software implementation and testing, input/output file transfer confirmation, and developing process control in FY2007. Operational data processing will begin three months after the launch. The products will be provided to researchers and general users after validation is complete. Keywords: GOSAT, Greenhouse gases, CO2, CH4, Source/sink flux

－ 113 －

－ 113 －


Project name: Application of the Transport Model for Inverse Modeling Studies of the Regional and Global Budgets of CO2 Project leader: Shamil MAKSYUTOV, National Institute for Environmental Studies Project members: Tomoko SHIRAI, Dmitry BELIKOV, Nikolay KADYGROV, Yuji KOYAMA, Yumiko NAKATSUKA, Vinu VALSALA, Anna PEREGON, Makoto SAITO, National Institute for Environmental Studies Yosuke NIWA, Ryoichi IMASU, Center for Climate System Research, The University of Tokyo Abstract:

We used inverse model of the atmospheric CO2 transport for adjusting parameters of the global atmospheric transport model to fit seasonal cycle of the observed concentration in the atmospheric column, which is stable against errors and biases in the model vertical mixing parameterizations. The data from several airborne observation sites globally were used as summarized in GLOBALVIEW dataset. The analysis was made using NIES tracer transport model run on NIES supercomputer. An inverse model of the model parameters for 11 vegetation types of a terrestrial biosphere flux model was used to optimize the surface monthly CO2 fluxes. The results show good agreement with simulated CO2 seasonal cycle in free troposphere. The same (i.e. optimized) global flux dataset was used in validation of the updated version of the global tracer transport model. Transport model was improved by adding a wind correction that guarantees exact mass conservation, and higher order advection algorithm. Comparison with vertical profile observation show better model performance compared to previous version. Additionally, frequent observation of the atmospheric CO2 over Japan was used for model performance evaluation. Keywords: Atmospheric CO2, Global transport model, Synoptic scale variability, Continuous observations, Terrestrial biosphere model, Satellite remote sensing

－ 114 －－ 115 －

Application of the Transport Model for Inverse Modeling Studies of the Regional and Global Budgets of CO2

Project name: Application of the Transport Model for Inverse Modeling Studies of the Regional and Global Budgets of CO2


Project leader: Shamil MAKSYUTOV, National Institute for Environmental Studies Project members: Tomoko SHIRAI, Dmitry BELIKOV, Nikolay KADYGROV, Yuji KOYAMA, Yumiko NAKATSUKA, Vinu VALSALA, Anna PEREGON, Makoto SAITO, National Institute for Environmental Studies Yosuke NIWA, Ryoichi IMASU, Center for Climate System Research, The University of Tokyo 1. Purpose

Purpose of the research is to provide forward and inverse model analysis of the spatial and temporal variations of the greenhouse gas concentrations and surface fluxes. This year focus is on the analysis of the vertical profiles and column abundance of the atmospheric CO2.

Keywords: Atmospheric CO2, Global transport model, Synoptic scale variability, Continuous observations, Terrestrial biosphere model, Satellite remote sensing 2. Record of the Supercomputer Uses 2.1 Devoted Computing Time

CPU time Total : 1,827hrs 2.2 Details of the Application of the Supercomputer

The NIES atmospheric transport model was ran using the NIES supercomputer. Using this model, the transports of several atmospheric tracers as well as the “response functions” for the atmospheric inversion were simulated.

3. Progress and Results of the Research: Forward and Inverse Model Study with the Airborne Observation Data in Optimizing Seasonality of Global Terrestrial Carbon Cycle; Model Tuning; and Validation. 3.1. Abstract

We used inverse model of the atmospheric CO2 transport for adjusting parameters of the global atmospheric transport model to fit seasonal cycle of the observed concentration in the atmospheric column, which is stable against errors and biases in the model vertical mixing parameterizations. The data from several airborne observation sites globally were used as summarized in GLOBALVIEW dataset. The analysis was made using NIES tracer transport model. An inverse model of the model parameters for 11 vegetation types was used to optimize the surface monthly CO2 fluxes. The results show good agreement with simulated CO2 seasonal cycle in free troposphere. The same (i.e. optimized) global flux dataset was used in validation of the updated version of the global tracer transport model. Transport model was improved by adding a wind correction that guarantees exact mass conservation, and higher order advection algorithm. Comparison with vertical profile observation show better model performance compared to previous version. Additionally, frequent observation of the atmospheric CO2 over Japan was used for model performance evaluation. 3.2 Introduction

In our research project, we make effort to produce better simulation of the vertical profiles and column averaged concentration of the atmospheric CO2 in order to design an optimal set of the fluxes and process

－ 114 －－ 115 －


parameterizations for use in simulation of a first guess for Greenhouse gases Observing SATellite (GOSAT) CO2 retrievals. To accurately simulate a seasonal cycle of the CO2 total column, we optimized the terrestrial flux model by fitting simulated CO2 flux to the observed total and partial column CO2 observations. Model transport algorithm is also being updated to make it suitable for use in data assimilation type of inverse modeling, which requires derivation of adjoint, with extra needs for more strict linearity and mass conservation. Due to earlier finding (Yang et al., 2007) on bias due to possible weak vertical mixing, we made comparison of the update transport model with observations after applying the flux correction based on free tropospheric data. Additionally, we made model comparison with newly available very-frequent airborne observation data over Narita.

3.3 Optimization of CASA Model Parameters with Observed Partial-column Concentration of CO2 3.3.1 Method

Parameters of a terrestrial biosphere model were optimized using observed seasonal cycles of CO2 and an atmospheric transport model. Two parameters (light use efficiency Emax and soil respiration response factor Q10) of Carnegie-Ames-Stanford Approach (CASA) model were optimized for each of 11 vegetation types recognized in CASA (Potter et al., 1993). The parameter-inversion method is described by Maksyutov et al. (2008a) except some minor changes described below. We minimized the difference between the partial column concentrations of observed and simulated CO2 seasonal cycles. The observed seasonal cycles of partial column concentrations were prepared from the seasonal cycles of 17 vertical profiles of CO2 from Northern Hemisphere available from GLOBALVIEW-CO2 (2007). We chose to use the partial column data of CO2, instead of discrete CO2 concentration data, because we previously found that the optimization of flux model parameters with the discrete CO2 concentration data is sensitive to even a slight defect of the model’s vertical transport scheme and that we can avoid this effect by using the partial (or whole) column data of CO2 concentrations (Nakatsuka et al., in preparation). Moreover, the transport model used for this study was a flux-form version with van Leer advection model with 2.5° × 2.5° horizontal resolution (described in the section 3.4 below). Fig. 1. Comparison of initial and optimized CO2 vertical profiles with the observed ones. Winter is defined here as an average of January-February-March and summer as an average of July-August-September. CAR: Carr, Colorado; ESP: Estevan Point, Canada; HAA: Hawaii Air; HFM: Harvard Forest, Massachusetts; ORL: Orleans, France; PFA: Poker Flat, Alaska; TGC: Sinton, Texas; THD: Trinidad Head, California; ZOT: Zotino, Russia.

8000

7000

6000

5000

4000

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5000

4000

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-8 -6 -4 -2 0 2 4

6000

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Alti

tude

(m)

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TGC THD ZOT

Initial (summer) Initial (winter)

Optimized (summer) Optimized (winter)

Observed (summer) Observed (winter)

－ 116 －－ 117 －


3.3.2 Results The initial values of Emax and Q10 were chosen to be 0.55 ( 0.165) gC/ MJ PAR and 1.50 ( 0.15),

respectively, and 5 iterative calculations were carried out. The vertical profiles of CO2 resulting from CASA with initial (i.e. before optimization) and optimized parameters are shown along with the observed vertical profiles (Fig. 1). It can be seen that the seasonal cycle of the CO2 concentration at these stations were improved dramatically by the optimization. At the same time, it can also be seen from Fig. 1 that the vertical mixing in the model has some weakness, especially in winter. Therefore, unless the vertical scheme itself is optimized, the optimization of CASA (or any flux model) with the discrete CO2 concentration data is not plausible. 3.4 Introducing Mass-conserving Winds and Van Leer Advection to NIES Global Transport Model and Validation with CO2 Seasonal Cycle over Siberia 3.4.1. Method

New version of NIES global transport model designed to simulate the seasonal cycles of the long-lived tracer species is reported in this section. The transport model has been improved recently by increasing spatial resolution and driven by diurnal cycle resolving meteorology for simulating diurnal-synoptic scale variations (Maksyutov et al., 2008b). However, the modification of the model is necessary to be used efficiently in tracer transport and surface flux assimilation studies. Most serious demand is in linearity and mass conservation. Semi-lagrangian approach used by Maksyutov et al. (2008b) provides linearity without placing any limitations on time step, but has to be supported by mass fixer. Another approach is to use flux-form method, which also requires a dry-air mass conserving mass fluxes to be tracer-mass conservative (see Bergman et al., 2003). We implemented a simple horizontal mass flux correction procedure, based on Poisson equation solver utilizing a 2-D FFT program. For tracer transport, a second order van Leer scheme (van Leer, 1977) for advection was implemented in the model. In van Leer scheme we can write advective flux 1i

wU of dependent variable 1iP through the border w of finite volume using variable slope wS

between border w and value of grid variable from nearest upwind node:

1 1

1

1 1

1 , 0;21 , 0.2

i i iW w ww

iw

i i iP w ww

U S x UU

U S x U

(1)

where x is grid spacing in x direction, 1i

wU is Cartesian velocity components in x direction as shown

in Fig. 2, 1i is a new time step, and i is the old time step.

SW S

E

SS

N

NN

W EEWW P ew

s

n

y

x

SE

NW NE

y

x

Fig. 2. Model grid.

－ 116 －－ 117 －


For slope wS we used formula without monotonicity fixers, in order to preserve linearity, which is important for simplified derivation of tangent linear adjoint:

, 0;12 , 0.

E Ww

w dWW P

w

UxS v

Ux

(2)

In equation 2, dv is an extra diffusion to dump amplification. Second order linear upwind van Leer scheme is more accurate then previously implemented simple upstream scheme. Same way as in the previous version (Maksyutov and Inoue, 1999), we used reduced grid with aggregated cells near the pole of a type introduced by Kurihara (1965), to avoid time step limitations due to small grid size near the pole. For simplicity, only 1:1 and 1:2 ratios of adjacent grid cell size were allowed. 3.4.2 Results

We found that the combination of optimized CASA flux (described in the section 3.3 above) and the flux-form transport model developed in this study resulted in a stronger and better seasonality of CO2 than the combination of un-optimized flux and the semi-Lagrangian type transport model (Fig. 3). To check model performance with new set of fluxes, model with 2.5°×2.5° horizontal resolution (i.e. 144×72 meshes) and 12-hour meteorological NCEP data was used.

To validate model against high resolution concentration timeseries, CO2 observations at Hateruma station were used. We simulated CO2 concentration using model with 2.5°×2.5° horizontal resolution (i.e. 144×72 meshes), 12-hour meteorological NCEP and ocean, fossil, optimized Net Ecosystem Production (NEP) fluxes as well. Comparison between model and observation after subtraction of annual average and seasonal cycle is presented on Fig. 4.

1 2 3 4 5 6 7 8 9 10 11 12Month

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-5

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b i d l

h=500m

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1 2 3 4 5 6 7 8 9 10 11 12Month

-10

-5

0

5

10CO2,ppm

h=1000m

h=3000m h=4000m h=7000m

h=2000m

Fig. 3. Seasonal variation of CO2 at different altitudes (h) for 1996 at Novosibisk station. Green triangles: biospheric fluxes without optimization and semi-Lagrangian transoprt model; red diamonds: optimized fluxes and flux-form transport model; blue crosses: observations.

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Fig. 4. Synoptic scale variation of CO2 at Hateruma station during 2002. 3.5 Model Comparison with CONTRAIL Observations over Narita 3.5.1 Method

The CO2 concentrations in free troposphere simulated by the NIES tracer transport model (NIES_TM) were compared with those obtained by the aircraft measurement: CONTRAIL (Comprehensive Observation Network for TRace gases by AIrLiner) (Machida et al., 2008). First, we checked the general feature of the model results and compared the effect of changing the horizontal resolution of the model grids (2.5°×2.5° to 1°× 1°) and using different model version (the frequency of input meteorological data changed from every 12 hours to every 3 hours) to the model performance. The comparison of horizontal model resolution change was conducted using the NIES_TM ver.99 (Maksyutov et al., 2008b) with CASA monthly flux and 12 hourly NCEP data input, and the results was compared with the NIES_TM ver.05 with CASA 3hourly flux and 3 hourly NCEP data input. The fossil fuel flux and the ocean flux used are the same as the previous section (3.3.1). 3.5.2 Results

Fig. 5 shows the CO2 concentrations in 5 km altitude simulated for the grid over the Narita Airport (140-141°E, 35-36°N in 1°×1° grid and 140-142.5°E, 35-37.5°N in 2.5°×2.5° mesh grid).

Fig. 5. Simulated (blue/green/orange lines) and Observed CO2 mixing ratios (black dots) in 5 km over the Narita Airport. The absolute values of the simulation results have been adjusted but the scale has not been adjusted. Details about the different setting of simulation are explained in the text.

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The model reproduced the timing and the amplitude of the seasonal variation fairly well except the NIES_TM ver.05 (v05d1.0 in Figure 5) which underestimated the amplitude as the orange line in the Figure 5. The most possible factor among the difference between NIES_TM ver.99 and ver.05 was the convection scheme. The weak convection in the NIES_TM may have resulted in the smaller amplitude of the CO2 seasonal cycle in the free troposphere. The development of the more realistic convection scheme is currently conducted as shown in the previous section (3.3.2).

The performance of the models was also checked by the comparing how each model expresses the synoptic-scale variation (~days) of CO2 mixing ratios. The most distinctive difference when changing the model grids resolution from 2.5°×2.5° to 1°×1° (v99d2.5 and v99d1.0 respectively in Fig. 5) was the higher amplitude of synoptic variation. The range of variation almost doubled from approximately ±1 ppm to ±2 ppm which is closer to the range of observed synoptic variation.

Fig. 6. Simulated (blue/green/orange lines) and Observed CO2 mixing ratios (black dots) in 5 km over the Narita Airport as shown in Figure 5. The surface pressure at the same horizontal grid of 1°x 1° run is shown as the purple dotted line.

An example of the observed/simulated synoptic variations is shown in Fig. 6. The surface pressure (PS) for the same location (NCEP data converted to 1°×1° mesh) is also shown as an indicator of the local weather. The sharp drops of PS indicate the passage of low-pressure systems. The higher CO2 mixing ratios often observed when the PS was low suggesting the passage of cyclones is one of factors controlling the CO2 mixing ratios in the free troposphere. Simulated CO2 mixing ratios also showed increase at the timing as shown on Oct. 29th and Nov.11th ~12th in Fig. 6, but the anti-correlation between simulated CO2 mixing ratios and the PS was not significant. When comparing the different model settings, The effect of changing model horizontal resolution contributed to make peaks sharper but did not significantly changed the timing of the peak whereas the increase of the resolution and the frequency of input meteorological data showed finer time-scale variation which significantly changed the timing of the peaks in some cases. The time-scale of the fluctuation of both observed and simulated CO2 mixing ratios was slightly shorter than that of the surface pressure. This indicates that there are other factors contributing its synoptic variation. The discrepancy between the observed and simulated CO2 must be the mixed effect from the discrepancy in the transport and the flux distributions. We have to check other meteorological parameters such as the horizontal wind field and vertical flow as well as estimating the location of the flux affecting the CO2 field.

Previous study which compared the result of the NIES_TM in different horizontal resolution using surface CO2 observation (Maksyutov et al., 2008b) noted that higher resolution results could capture the synoptic scale variability better than lower resolution setting particularly when CO2 was transported mainly from nearby source region. In case of the free troposphere, CO2 variation can be more affected by the long-range transport and the vertical mixing. The next step is to find out important controlling factors for the

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CO2 variation in the free troposphere depending on the season, and possibly quantify the fraction of the contribution from each factor. As the observation is based on the data obtained during the ascent and descent of the airplanes, we have to check the spatial representativeness of observed data relative to the model grid cubic. Concurrently, the extent of homogeneity/inhomogeneity of the CO2 field in the vicinity of observation points should be checked with help of simulation results and available meteorological data.

References Bregman, B., Segers, A., Krol, M., Meijer, E., van Velthoven, P. (2003) On the use of mass-conserving wind

fields in chemistry-transport models, Atmos. Chem. Phys., 3, 447-457. GLOBALVIEW-CO2 (2007) Cooperative atmospheric data integration project - carbon dioxide., in, CD-ROM,

NOAA ESRL, Boulder, Colorado [Also available on Internet via anonymous FTP to ftp.cmdl.noaa.gov, Path: ccg/co2/GLOBALVIEW].

Kurihara, Y. (1965) Numerical integration of the primitive equations on a spherical grid. Monthly Weather Review, 93(7), 399-416.

Machida, T., Matsueda, H., Sawa, Y., Nakagawa, Y., Hirotani, K., et al. (2008) Worldwide measurements of atmospheric CO2 and other trace gas species using commercial airlines. Journal of Atmospheric and Oceanic Technology, in press.

Maksyutov, S. et al. (2008a) Application of the transport model for inverse modeling studies of the regional and global budgets of CO2, NIES Supercomputer Annual Report 2006, CGER-I078-2008, 23-32.

Maksyutov, S., Patra, P.K., Onishi, R., Saeki, T., Nakazawa, T. (2008b) NIES/FRCGC global atmospheric tracer transport model: description, validation, and surface sources and sinks inversion, J. of Earth Simulator, 9, 3-18.

Maksyutov, S., Inoue, G. (1999) Global tracer transport model simulations of CO2 variations over Eurasia. - In: CGER Supercomputer activity report, CGER-I034’99, CGER, NIES, Japan, 6, 33-35

Nakatsuka, Y., Maksyutov, S. et al. (in preparation) Optimization of the seasonal cycles of simulated CO2 flux and effects of weak vertical mixing in a transport model.

Potter, C. S., Randerson, J. T., Field C. B. et al. (1993) Terrestrial ecosystem production: A process model based on global satellite and surface data. Global Biogeochem. Cycles, 7, 811-841.

van Leer, B. (1977), Towards the ultimate conservative difference scheme: IV, a new approach to numerical convection, J. Comp. Phys, 23, 276-299.

Yang, Z., Washenfelder, R. A., Keppel-Aleks, G., Krakauer, N. Y., Randerson, J. T., et al. (2007) New constraints on Northern Hemisphere growing season net flux. Geophys. Res. Lett., 34, L12807, doi:10.1029/2007GL029742.

4. Conclusions

Several improvements to the atmospheric transport model and model of the surface CO2 fluxes were made. Parameters of CASA terrestrial biosphere model were optimized using the observed CO2 concentrations in free troposphere in conjunction with atmospheric transport model and Bayesian inversion technique. The optimized fluxes were found to be stronger than the basic ones but appear to reproduce the seasonal variability over continents equally well both in Planetary Boundary Layer (PBL) and free troposphere with the updated version of the flux form tracer transport model based on mass-conservation-adjusted wind field. The second order flux form transport algorithm was implemented and tested. The algorithm uses a reduced longitude-latitude grid suitable for efficient simulations even at high spatial resolution.

The model simulation of the seasonal and synoptic scale variability over Narita was tested against recent very frequent observations of CO2 vertical profiles conducted on JAL airplanes; better correlation with observation was achieved in upper troposphere while an lower troposphere the synoptic scale variability is not yet captured by model.

5. Future Plan

We plan to test newly developed modeling tools and surface fluxes in research and development for GOSAT data analysis, evaluate the modeling tools by estimation the spatial and temporal variability of the inverse model-derived fluxes.

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6. List of Publications 6.1 Peer-reviewed Articles Maksyutov, S., Patra, P.K., Onishi, R., Saeki, T., Nakazawa, T. (2008) NIES/FRCGC global atmospheric tracer

transport model: description, validation, and surface sources and sinks inversion, JES, 9, 3-18. Law, R., et al. (2008) Transcom Model simulation of hourly atmospheric CO2: experimental overview and

diurnal cycle results for 2002, GBC., 22, GB3009, doi:10.1029/2007GB003050. Valsala, V., Maksyutov, S., Ikeda, M. (2008) Design and validation of an offline Oceanic Tracer Transport

Model for Carbon Cycle study, J. Climate, 21(12), 2752-2769. Maksyutov, S., Kadygrov, N., Nakatsuka, Y., Patra, P. K., Nakazawa, T., Yokota, T., Inoue, G. (2008) Projected

impact of the GOSAT observations in regional CO2 flux estimations as a function of total retrieval error, J. Remote Sensing Society of Japan, 28(2).

6.2 Oral Presentations Maksyutov, S., Carouge, C., Kadygrov, N., Koyama, Y., Nakatsuka, Y., Peregon, A., Valsala, V., Machida, T.,

Yokota, T., Patra, P., Nakazawa, T. (2007) Towards development of the operational system for GOSAT CO2 data use in the inverse model of the atmospheric CO2 transport, 3rd IWGGMS, Paris, June 2007.

Maksyutov, S., Machida, T., Kadygrov, N., Carouge, C., Peylin, P., Patra, P. (2007) Study of the regional carbon fluxes though inverse modeling of the Siberian atmospheric CO2 observations, Invited, AGU Fall meeting, San Franscisco, Dec 2007.

Maksyutov, S., Nakatsuka, Y., Belikov, D., Valsala, V. (2008) Atmospheric CO2 simulation with optimized surface flux climatology for use in GOSAT CO2 retrieval, EGU General Assembly, Vienna, April 2008.

Maksyutov, S. (2008) Atmospheric greenhouse gas studies in North Eurasia at NIES, NEESPI Workshop, MPI BGC, Jena, March 2008.

7. Contact Person Shamil Maksyutov, National Institute for Environmental Studies 16-2 Onogawa, Tsukuba, Ibaraki 305-8506 Tel: 029-850-2212 Fax: 029-850-2219 E-mail: [email protected]

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CO2

14 19

Shamil MAKSYUTOV

Dmitry BELIKOV Nikolay KADYGROV Vinu VALSALA Anna PEREGON

NIES

19

GLOBALVIEW

NIES11

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20053 4 ABC-

EAREX2005 EANET Acid Deposition Monitoring Network in East AsiaPILS PM2.5 PM10

PSAPGEOS/chem

1%50 90%

3.0 g/m3 3.44 g/m3 17.0%

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8 19

1.

km

2. 2.1

CPU Total 0hr

2.2 3 MSSP

3. 3.1

2005 3 4ABC-EAREX2005 EANET Acid Deposition

Monitoring Network in East Asia

3.2

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GER-I086-2008, CGER/NIES

3.3 MSSP Kajino et al., 2005

100 70 60 km 10 km 12NCEP/FNL, ds083.2

WRF/ARW Ver2.2 TOMSStreets et al. 2003;

2006 EDGAR3.2 GFED2 VOC GEIAGOES/chem., Park et al., 2004

MODIS LAIWhitby and McMurry, 1997

ABC-EAREX2005 2005 3 12 411 1 1

1 MSSP

PILS Particle Into Liquid Sampler PM2.5 PM10

PSAP Particle Soot Absorption Photometer EANET

3.4 PILS PM2.5 PM10 PSAP

ON/OFF3

26.0 53.0 16.8 7.1 18.6 19.2 g/m3

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1%50 90% 2

3.0 g/m3 3.44 g/m3 17.0%

2 ABC-EAREX2005 PM2.5 g/m3

GEOS-chem

Kajino, M., Ueda, H., Satsumabayashi, H., Han, Z. (2005) Increase in nitrate and chloride deposition in East Asia due to increased sulfate associated with the eruption of Miyakejima Volcano. J. Geophys. Res. 110, D18203, doi:10.1029/2005JD005879.

Park, R. J., Jacob, D. J., Field, B. D., Yantosca, R. M., Chin, M. (2004) Natural and transboundary pollution influences on sulfate-nitrate-ammonium aerosols in the United States: Implications for policy. J. Geophys. Res. 109, D15204, doi:10.1029/2003JD004473.

Streets, D. G. et al. (2003) An inventory of gaseous and primary aerosol emissions in Asia in the year 2000, J. Geophys. Res. 108, D21, 8809, doi:10.1029/2002JD003093.

Streets, D. G. et al. (2006) Revisiting China’s CO emissions after the Transport and Chemical Evolution over the Pacific (TRACE-P) mission: Synthesis of inventories, atmospheric modeling, and observations. J. Geophys. Res. 111, D14306, doi:10.1029/2006JD007118.

Whitby, E. R., Mcmurry, P. H. (1997) Modal Aerosol Dynamics Modeling. Aerosol Science and Technology. 27, 673-688.

4.

PILS PM2.5 PM10PSAP

ON/OFF

5.

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6. 6.1 Kajino, M., Ueda, H., Nakayama, S. (2008) Secondary acidification: Changes in gas-aerosol partitioning of

semi-volatile nitric acid and enhancement of its deposition due to increased emission and concentration of SOx. J. Geophys. Res. 113, D03302, doi:10.1029/2007JD008635.

Kajino, M., Ueda, H. (2007) Increase in nitrate deposition as a result of sulfur dioxide emission increase in Asia: indirect acidification, Air Pollution Modeling and its Application XVIII, 134-143.

6.2 Kajino, M., Nakayama, S., Gromov, S., Ueda, H. (2007) Enhanced deposition of semi-volatile aerosol

components caused by increase in SO2 emission. 10th International Conference on Atmospheric Sciences and Applications to Air Quality, Hong Kong, China.

7.

950-2144 1182


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Project name: Atmospheric Motion and Air Quality in East Asia 1996 April - 2008 March Project leader: Hiromasa UEDA, Acid Deposition and Oxidant Research Center Project members: Shiro HATAKEYAMA, Tokyo University of Agriculture and Technology Kentaro MURANO, National Institute for Environmental Studies Shinji NAKAYAMA, Ayako AOYAGI, Acid Deposition and Oxidant Research Center Mizuo KAJINO, Research Center for Advanced Science and Technology, The University of Tokyo Abstract:

Atmospheric aerosols play important rules on climate and meteorology changes by scattering and absorbing solar radiation, changing cloud optical properties, and prolonging cloud lifetimes. This study develops a regional-scale aerosol chemistry transport model in order to accurately assess these impacts. The model explicitly considers chemical components, size distribution, mixing state and particle shape, which affects aerosol radiation properties and activation processes substantially. The model performance is evaluated by comparing with the aerosol concentration data from the ground-based field observation at Cheju Island, Korea, during ABC-EAREX campaign, as well as with concentration and wet deposition data monitored in EANET (Acid Deposition Monitoring Network in East Asia). The model well reproduced PM2.5 and PM10 inorganic aerosol components and black carbon concentrations measured by PILS and PSAP, respectively, in the contaminated outflow from the Asian continent in spring 2005. Another simulation is performed with lateral and upper boundary conditions derived from a global chemical transport model (GEOS/chem.) to evaluate the transport from outside East Asia. During the outflow transport events, the contribution of outside of the boundaries is less than 1% for surface sulfate aerosol concentration at Cheju Island, while anti-cyclonic transport events carries 50-90% of sulfate aerosols from outside East Asia. Monthly mean concentration of sulfate aerosol was 3.0 m/m3 observed and 3.44 m/m3 simulated, and the contribution is 17%. The contribution to surface aerosol concentrations on a monthly basis from transport outside East Asia is not negligible at Cheju Island. Keywords: Regional-scale Meteorological Model, Aerosol chemistry transport model, Sulfate, Nitrate

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2007 3 NEC SX-8R/128M16OS SUPER-UX SX-6/64M8

SX-8R/128M16NEC Express5800/120Ri-2 SGI Origin35

HP ProLiant DL585

SX-8R/128M16 4.096 TFLOPS 1 256GFLOPS

1.536 TB 128GB/node 8, 64GB/node 830TB 320TB

16GB/s IXS

1000BASE-SX

SX-8R

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1 . SX-8R

1.1 2007 3 NIES NEC

SX-8R SX-8R/128M16 SUPER-UXSX-6/64M8

SX-8R 1

1

NEC Express5800/120Ri-2SGI Origin350 HP ProLiant DL585

SX-8R/128M16 4.096 TFLOPS 256 GFLOPS

1.536 TB 128GB/node 8, 64GB/node 8 30TB 320TB

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16GB/s IXS 1000BASE-SX

SX-8R Express5800/120Ri-2 NFS CXFS

1.2 1.2.1 SX-8R

SX-8R 16 SX-8R 2.0 GHzCPU 32 GFLOPS 256 GFLOPS

512GB/s 16 GB/s

1Linpack 3,640

GFLOPS 495 GFLOPSSTREAM 6,560 GB/s 1,600 GB/s

1

SX-6/64M8 SX-8R/128M16 8 nodes 16 nodes

CPU 64 CPUs 128 CPUs 512 GFLOPS

64 GFLOPS/node4.096 TFLOPS

256 GFLOPS/node512 GB

64 GB x 8 nodes1.536 TB

128 GB x 8 nodes64GB x 8 nodes

SX-8R SX-6

1.2.2 Xeon5100CPU Intel Xeon 5160 3GHz 2

NEC Express5800/120Ri-2 InfiniBand 10Gbps

1.2.3

NEC iStorage SGI Infinite Storage

SX-8R I/O SAN GFSI/O

SAN CXFS

HSM

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2 .

2.1 CPUsingle 300,884 hoursmulti 269,097 hours

Total 569,981 hours

2.2 2.2.1

19 2 3

2

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CPUv_deb 8 2 2H 0.6H 62GB 1 4 scvec16

v_cpu 1 4CPU 8 5 24H 26.6H 62GB 1 4 scvec16

v_01n 1node 15 3 96H 13.2H 124GB 5 8 scvec01 - scvec15

v_2nA 2node 3 1 96H/node 13.2H 62GB/node 9 16 scvec03 - scvec08

v_2nB 2node 3 1 96H/node 13.2H 124GB/node 9 16 scvec10 - scvec15

v_4nA 4node 1 96H/node 13.2H 62GB/node 17 32 scvec03 - scvec08

v_4nB 4node 1 96H/node 13.2H 124GB/node 17 32 scvec10 - scvec15

v_15n 15node 1 5760H/node 792H 62GB/node 33 112 scvec01 - scvec15

1

3

CPU

s_single 4 72H 8GB/host scsl01 s_p4 4 CPU 3 72H 8GB/host scsl02 - scsl04 s_p8 8 CPU 2 72H 8GB/host scsl05 – scsl08 s_p16 16 CPU 1 72H 8GB/host scsl09 – scsl12 s_p32 32 CPU 1 72H 8GB/host scsl13 – scsl20

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2.2.2 19 SX-8R 2 19 8

10 9 12

2 19

3 .

NQSII/ERSII

3.1 NQSII 3.1.1

SUPER-UX NQSII CPU

NQSII

3.1.2 SUPER-UX NQSII

JOB-COUNT、CPU-TIME

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0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar

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10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

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job-count(all job)

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cpu-time(all job)

cpu-time(multi-node job)

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ERSII

CPU MFF

CPU

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Overview of the NIES Supercomputer Systems Environmental Information Center, National Institute for Environmental Studies NEC Corporation Abstract:

In March 2007 the National Institute for Environmental Studies (NIES) replaced its SX-6/64MB system with a NEC SX-8R/128M16 supercomputer system running the SUPER-UX OS. The system is configured with the SX-8R (for the vector calculations server) and the other central machines; NEC Express5800/120Ri-2 (for the scalar calculations server and front-end server), SGI Origin350, HP ProLiant DL585, and so on. The network utilizes a gigabit ethernet switch.

The SX-8R/128M16 provides peak vector performance of 4.096 TFLOPS (256 GFLOPS per node),

and has the following features:

-1.536 TB of main memory (64GB per node x8, 128GB per node x8) -large scale file system (about 30 TB of raid disk for the front-line disk; about 320 TB for near-line disk) -large capacity tape library -internode crossbar switch (IXS) interface at 16 GB/s -1000BASE-SX interface at 1 Gbps

Keywords: SX-8R, Vector computing, Scalar computing, Large scale memory, Large file system

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CGER’S SUPERCOMPUTER ACTIVITY REPORT

Vol. 1-1992 (CGER-I010-’94) Vol. 8-1999 (CGER-I043-2000) Vol. 2-1993 (CGER-I016-’94) Vol. 9-2000 (CGER-I050-2002) Vol. 3-1994 (CGER-I020-’95) Vol.10-2001 (CGER-I054-2002) Vol. 4-1995 (CGER-I024-’96) Vol.11-2002 (CGER-I058-2004) Vol. 5-1996 (CGER-I030-’97) Vol.12-2003 (CGER-I061-2005) Vol. 6-1997 (CGER-I034-’99) Vol.13-2004 (CGER-I064-2006) Vol. 7-1998 (CGER-I039-2000) Vol.14-2005 (CGER-I070-2007)

NIES Supercomputer Annual Report

18 2006 (CGER-I078-2008)

CGER’S SUPERCOMPUTER MONOGRAPH REPORT

Vol. 1 CGER-I021-’96 (Out of stock) Turbulence Structure and CO2 Transfer at the Air-Sea Interface and Turbulent Diffusion in Thermally-Stratified Flows

Vol. 2 CGER-I022-’96 A Transient CO2 Experiment with the MRI CGCM: Annual Mean Response

Vol. 3 CGER-I025-’97 Study on the Climate System and Mass Transport by a Climate Model

Vol. 4 CGER-I028-’97 (Out of stock) Development of a Global 1-D Chemically Radiatively Coupled Model and an Introduction to the Development of a Chemically Coupled General Circulation Model

Vol. 5 CGER-I035-’99 Three-Dimensional Circulation Model Driven by Wind, Density, and Tidal Force for Ecosystem Analysis of Coastal Seas

Vol. 6 CGER-I040-2000 Tropical Precipitation Patterns in Response to a Local Warm SST Area Placed at the Equator of an Aqua Planet

Vol. 7 CGER-I045-2001 New Meteorological Research Institute Coupled GCM (MRI-CGCM2): Transient Response to Greenhouse Gas and Aerosol Scenarios

Vol. 8 CGER-I055-2003 (Out of stock) Transient Climate Change Simulations in the 21st Century with the CCSR/NIES CGCM under a New Set of IPCC Scenarios

Vol. 9 CGER-I057-2004 Vortices, Waves and Turbulence in a Rotating Stratified Fluid

Vol.10 CGER-I060-2005 Modeling of Daily Runoff in the Changjiang (Yangtze) River Basin and its Application to Evaluating the Flood Control Effect of the Three Gorges Project

Vol.11 CGER-I063-2006 Development of Process-based NICE Model and Simulation of Ecosystem Dynamics in the Catchment of East Asia (Part I)

Vol.12 CGER-I073-2007 Climate Change Simulations with a Coupled Ocean-Atmosphere GCM Called the Model for Interdisciplinary Research on Climate: MIROC

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Vol.13 CGER-I080-2008 Simulations of the Stratospheric Circulation and Ozone during the Recent Past (1980-2004) with the MRI Chemistry-Climate Model

Vol.14 CGER-I083-2008 Development of Process-based NICE Model and Simulation of Ecosystem Dynamics in the Catchment of East Asia (Part II)

http://www-cger.nies.go.jp/cger-j/report/r_index-j.html PDF

These reports are available as a PDF file. See: http://www-cger.nies.go.jp/cger-e/e_report/r_index-e.html

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[CGER-REPORT : ISSN 1341-4356, CGER-I086-2008]

2008 10

305-8506 16-2

029-850-2347 FAX 029-858-2645 E-mail [email protected] http://www.nies.go.jp/index-j.html

NIES Supercomputer Annual Report 2007CGER-REPORT ISSN 1341-4356 CGER-I086-2008 国立環境研究所スーパーコンピュータ利用研究年報 平成19 年度 NIES Supercomputer

Documents

NIES Supercomputer Annual Report 2007CGER-REPORT ISSN 1341-4356 CGER-I086-2008 国立環境研究所スーパーコンピュータ利用研究年報平成19 年度 NIES Supercomputer