Journal of the Korean earth science society (한국지구과학회지)

The Korean Earth Science Society (한국지구과학회)
권호 표지
DOI QR코드

DOI QR Code

An Installation and Model Assessment of the UM, U.K. Earth System Model, in a Linux Cluster

U.K. 지구시스템모델 UM의 리눅스 클러스터 설치와 성능 평가

  • Daeok, Youn (Department of Earth Science Education, Chungbuk National University) ;
  • Hyunggyu, Song (Department of Earth Science Education, Chungbuk National University) ;
  • Sungsu, Park (School of Earth and Environmental Sciences, Seoul National University)
  • 윤대옥 (충북대학교 지구과학교육과) ;
  • 송형규 (충북대학교 지구과학교육과) ;
  • 박성수 (서울대학교 지구환경과학부)
  • Received : 2022.12.06
  • Accepted : 2022.12.21
  • Published : 2022.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

The state-of-the-art Earth system model as a virtual Earth is required for studies of current and future climate change or climate crises. This complex numerical model can account for almost all human activities and natural phenomena affecting the atmosphere of Earth. The Unified Model (UM) from the United Kingdom Meteorological Office (UK Met Office) is among the best Earth system models as a scientific tool for studying the atmosphere. However, owing to the expansive numerical integration cost and substantial output size required to maintain the UM, individual research groups have had to rely only on supercomputers. The limitations of computer resources, especially the computer environment being blocked from outside network connections, reduce the efficiency and effectiveness of conducting research using the model, as well as improving the component codes. Therefore, this study has presented detailed guidance for installing a new version of the UM on high-performance parallel computers (Linux clusters) owned by individual researchers, which would help researchers to easily work with the UM. The numerical integration performance of the UM on Linux clusters was also evaluated for two different model resolutions, namely N96L85 (1.875° ×1.25° with 85 vertical levels up to 85 km) and N48L70 (3.75° ×2.5° with 70 vertical levels up to 80 km). The one-month integration times using 256 cores for the AMIP and CMIP simulations of N96L85 resolution were 169 and 205 min, respectively. The one-month integration time for an N48L70 AMIP run using 252 cores was 33 min. Simulated results on 2-m surface temperature and precipitation intensity were compared with ERA5 re-analysis data. The spatial distributions of the simulated results were qualitatively compared to those of ERA5 in terms of spatial distribution, despite the quantitative differences caused by different resolutions and atmosphere-ocean coupling. In conclusion, this study has confirmed that UM can be successfully installed and used in high-performance Linux clusters.

지구 대기에 영향을 주는 거의 모든 인간활동과 자연현상을 수치적으로 담아내는 지구시스템모델은 기후 위기의 시대에 활용될 가장 진보한 과학적 도구이다. 특히 우리나라 기상청이 도입한 지구시스템모델인 Unified Model (UM)은 지구 대기 연구의 과학적 도구로써 매우 활용성이 높다. 하지만 UM은 수치 적분과 자료 저장에 방대한 자원이 필요하여 개별 연구자들은 최근까지도 기상청 슈퍼컴퓨터에만 UM을 가동하는 상황이다. 외부와 차단된 기상청 슈퍼컴퓨터만을 이용하여 모델 연구를 수행하는 것은 UM을 이용한 모형 개선과 수치 실험의 원활한 수행에 있어 효율성이 떨어진다. 본 연구는 이러한 한계점을 극복할 수 있도록 개별 연구자가 보유한 고성능 병렬 컴퓨터(리눅스 클러스터) 에서 최신 버전 UM을 원활하게 설치하여 활용할 수 있도록 UM 시스템 환경 구축 과정과 UM 모델 설치 과정을 구체적으로 제시하였다. 또한 UM이 성공적으로 설치된 리눅스 클러스터 상에서 N96L85과 N48L70의 두 가지 모형 해상도에 대하여 UM 가동 성능을 평가하였다. 256코어를 사용하였을 때, 수평으로 1.875° ×1.25° (위도×경도)와 수직으로 약 85 km까지 85층 해상도를 가진 N96L85 해상도에 대한 UM의 AMIP과 CMIP 타입 한 달 적분 실험은 각각 169분과 205분이 소요되었다. 저해상도인 3.75° ×2.5° 와 70층 N48L70 해상도에 대해 AMIP 한달 적분은 252코어를 사용하여 33분이 소요되는 적분 성능을 보였다. 또한 적분을 위해 사용된 코어의 개수에 비례하여 적분 성능이 향상되었다. 성능 평가 외에 29년 간의 장기 적분을 수행하여 과거 지상 2-m 온도와 강수 강도를 ERA5 재분석자료와 비교하였고, 해상도에 따른 차이도 정성적으로 살펴보았다. 재분석자료와 비교할 때, 공간 분포가 유사하였고, 해상도와 대기-해양 접합에 따라 모의 결과에서 차이가 나타났다. 본 연구를 통해 슈퍼컴퓨터가 아닌 개별 연구자의 고성능 리눅스 클러스터 상에서도 UM이 성공적으로 구동됨을 확인하였다.

Keywords

Acknowledgement

이 연구는 기상청 <기후 및 기후변화 감시·예측정보 응용 기술개발> (KMI 2020-01110)의 지원으로 수행되었습니다. 본 논문의 완성도를 높이도록 검토 의견과 조언을 주신 편집위원님과 두 분의 심사위원님께 감사드립니다.

References

  1. Abraham, N.L., Archibald, A.T., Cresswell, P. et al., 2018, Using a virtual machine environment for developing, testing, and training for the UM-UKCA compositionclimate model, using Unified Model version 10.9 and above, Geoscientific Model Development, 11, 3647-3657. https://doi.org/10.5194/gmd-11-3647-2018
  2. Benacchio, T. and Wood, N., 2016, Semi-implicit semiLagrangian modeling of the atmosphere: a Met Office perspective, Communications in Applied and Industrial Mathematics, 7, 4-25. https://doi.org/10.1515/caim-2016-0020
  3. Calvin, K., Bond-Lamberty, B., Jones, A. et al., 2019, Characteristics of human-climate feedbacks differ at different radiative forcing levels, Global and Planetary Change, 180, 126-135. https://doi.org/10.1016/j.gloplacha.2019.06.003
  4. Chen, P.M., Lee, E.K., Gibson, G.A. et al., 1994, RAID: high-performance, reliable secondary storage, Association for Computing Machinery Computing Surveys, 26, 145-185.
  5. Cho, H.Y., Jun, T.J. and Han, J.Y., 2017, The Technology Trend of Interconnection Network for High Performance Computing, Journal of the Korea Convergence Society, 8, 9-15. (in Korean)
  6. Chung, S.W., Lee, C.H., Jeong, D.M., Yeom, G.H., 2021, A Survey of Weather Forecasting Software and Installation of Low Resolution of the GloSea6 Software, The Journal of Korea Institue of Information, Electronics, and Communication Technology, 14, 349-361.
  7. Collins, W.D., Craig, A.P., Truesdale, J.E. et al., 2015, The integrated Earth system model version 1: formulation and functionality, Geoscientific Model Development, 8, 2203-2219. https://doi.org/10.5194/gmd-8-2203-2015
  8. Cox, P.M., Betts, R.A., Jones, C.D. et al., 2000, Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model, Nature, 408, 184-187. https://doi.org/10.1038/35041539
  9. Craig, A., Valcke, S., and Coquart, L., 2017, Development and performance of a new version of the OASIS coupler, OASIS3-MCT_3.0, Geoscientific Model Development, 10, 3297-3308. https://doi.org/10.5194/gmd-10-3297-2017
  10. Cullen, M.J.P., 1993, The Unified Forecast/Climate Model, Meteorological Magazine, 122, 81-94.
  11. Danabasoglu, G., Lamarque, J.F., Bacmeister, J. et al., 2020, The Community Earth System Model Version 2 (CESM2), Journal of Advances in Modeling Earth Systems, 12, 1-35.
  12. Davies, T., Cullen, M.J.P., Malcolm, A.J. et al., 2005, A new dynamical core for the Met Office's global and regional modelling of the atmosphere, Quarterly Journal of the Royal Meteorological Society, 131, 1759-1782. https://doi.org/10.1256/qj.04.101
  13. Feng, X., Hodges, K.I., Hoang, L. et al., 2022, A New Approach to Skillful Seasonal Prediction of Southeast Asia Tropical Cyclone Occurrence, Journal of Geophysical Research: Atmospheres, 127, 1-24.
  14. Flato, G.M., 2011, Earth system models: an overview, WIREs Climate Change, 2, 783-800. https://doi.org/10.1002/wcc.148
  15. Gates, W.L., 1992, AMIP: The Atmospheric Model Intercomparison Project, Bulletin of the American Meteorological Society, 73, 1962-1970. https://doi.org/10.1175/1520-0477(1992)073<1962:ATAMIP>2.0.CO;2
  16. Griffies, S.M., Danabasoglu, G., Durack. P.J. et al., 2016, OMIP contribution to CMIP6: Experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project, Geoscientific Model Development, 9, 3231-3296. https://doi.org/10.5194/gmd-9-3231-2016
  17. Hersbach, H., Bell, B., Berrisford, P. et al., 2020, The ERA5 global reanalysis, Quarterly Journal of the Royal Meteorological Society, 146, 1999-2049. https://doi.org/10.1002/qj.3803
  18. Hill, C., Deluca, C., Balaji et al., 2004, The Architecture of the Earth system modeling framework, Computing in Science and Engineering, 6, 18-28.
  19. Hunke, Elizabeth, and Lipscomb, W., 2010, CICE: The Los Alamos Sea Ice Model Documentation and Software User's Manual Version 4.1, LA-CC-06-012, 76 p.
  20. Hurrel, J.W., Holland, M.M., Gent, P.R. et al., 2013, The Community Earth System Model: A Framework for Collaborative Research, Bulletin of the American Meteorological Society, 94, 1339-1360. https://doi.org/10.1175/BAMS-D-12-00121.1
  21. Ito, G., Romanou, A., Kiang, N.Y. et al., 2020, global Carbon Cycle and Climate Feedbacks in the NASA GISS Model E2.1, Journal of Advances in Modeling Earth Systems, 12, 1-44.
  22. Kawamiya, M., Hajima, T., Tachiiri, K. et al., 2020, Two decades of Earth system modeling with an emphasis on Model for Interdisciplinary Research on Climate (MIROC), Progress in Earth and Planetary Science, 7, 1-13. https://doi.org/10.1186/s40645-019-0311-0
  23. Koranne, S., 2011, Hierarchical Data Format 5 : HDF5. In: Handbook of Open Source Tools, 191-200, Springer, Boston, MA, USA.
  24. Madec, G, Delecluse, P, and Imbard, M, 1998, OPA 8.1 Ocean general circulation model reference manual, Note du Pole de Modelisation, 91 p.
  25. Manabe, S., and Stouffer, R.J., 1988, Two Stable Equilibria of a Coupled Ocean-Atmosphere Model, Journal of Climate, 1, 841-866. https://doi.org/10.1175/1520-0442(1988)001<0841:TSEOAC>2.0.CO;2
  26. Manabe, S., and Wetherald, R.T., 1975, The Effects of Doubling the CO2 Concentration on the Climate of a General Circulation Model. Journal of The Atmospheric Sciences, 32, 3-15. https://doi.org/10.1175/1520-0469(1975)032<0003:TEODTC>2.0.CO;2
  27. Manabe, S., Smagorinsky, J., and Strickler, R.F., 1965, Simulated Climatology of General Circulation with a Hydrologic Cycle, Monthly Weather Review, 93, 769-798. https://doi.org/10.1175/1520-0493(1965)093<0769:SCOAGC>2.3.CO;2
  28. Martin, G.M., Bellouin, N., Collins, W.J. et al., 2011, The HadGEM2 family of Met Office Unified Model climate configuration, Geoscientific Model Development, 4, 723-757. https://doi.org/10.5194/gmd-4-723-2011
  29. Meehl, G.A., Boer, G.J., Covey, C. et al, 2000, The Coupled Model Intercomparison Project (CMIP), Bulletin of the American Meteorological Society, 81, 313-318. https://doi.org/10.1175/1520-0477(2000)081<0313:TCMIPC>2.3.CO;2
  30. Morgenstern, O., Braesicke, P., O'Connor, F.M. et al., 2009, Evaluation of the new UKCA climate-composition model-Part 1: The stratosphere, Geoscientific Model Development, 2, 43-57. https://doi.org/10.5194/gmd-2-43-2009
  31. Oliver, H.J., Shin, M., Fitzpatrick, B. et al., Cylc-a workflow engine, available at: http://cylc.github.io/cylc/ (last access: 2 February 2022).
  32. Rew, R. and Davis, G., 1990, NetCDF: an interface for scientific data access, IEEE Computer Graphics and Applications, 10, 76-82. https://doi.org/10.1109/38.56302
  33. Schulte, M.J., Zelov, V., Akkas, A., and Burley, J.C., 1999, The Interval-Enhanced GNU Fortran Compiler, Reliable Computing, 5, 311-322. https://doi.org/10.1023/A:1009988620481
  34. Sellar, A.A., Jones, C.G., Mulcahy, J.P. et al., 2019, UKESM1: Description and Evaluation of the U.K. Earth System Model, Journal of Advances in Modeling Earth Systems, 11, 4513-4558. https://doi.org/10.1029/2019ms001739
  35. Shin, M., Fitzpatrick, B., Clark, A. et al., Rose: a framework for managing and running meteorological suites, available at: http://metomi.github.io/rose/doc/rose.html/ (last access: 2 October 2022).
  36. Shin, M., Fitzpatrick, B., Matthews, D. et al., FCM: Flexible Configuration Management, available at: http://metomi.github.io/fcm/doc/ (last access: 2 October 2022).
  37. Simmons, A., Fellous, J.L., Ramaswamy, V. et al., 2016, Observation and integrated Earth-system science: A roadmap for 2016-2025, Advances in Space Research, 57, 1-67. https://doi.org/10.1016/j.asr.2015.12.005
  38. Stallman, R.M., 1998, Using and Porting GNU CC, the Free Software Foundation, Boston, MA, USA, 391 p.
  39. Stott, P., 2016, How climate change affects extreme weather events, Science, 352, 1517-1518. https://doi.org/10.1126/science.aaf7271
  40. Thakur, R., Rabenseifner, R., and Gropp, W., 2005, Optimization of Collective Communication Operations in MPICH, The International Journal of High Performance Computing Applications, 19, 49-66. https://doi.org/10.1177/1094342005051521
  41. Tipka, A., Haimberger, L., Seibert, P., 2020, Flex_extract v7.1.2 - a software package to retrieve and prepare ECMWF data for use in FLEXPART, Geoscientific Model Development, 13, 5277-5310. https://doi.org/10.5194/gmd-13-5277-2020
  42. Walters, D.N., Best, M.J., Bushell, A.C. et al., 2011, The Met Office Unified Model Global Atmosphere 3.0/3.1 and JULES Global Land 3.0/3.1 configurations, Geoscientific Model Development, 4, 919-941. https://doi.org/10.5194/gmd-4-919-2011
  43. Xu, Q., Siyamwala, H., Ghosh, M. et al., 2015, Performance Analysis of NVMe SSDs and their Implication on Real World Databases, Association for Computing Machinery, 6, 1-11.
  44. Youn, D., Song, H., and Lee, J., 2022, Changes in Meteorological Variables by SO2 Emissions over East Asia using a Linux based U.K. Earth System Model, Journal of Korean Earth Science Society, 43, 60-76. (in Korean) https://doi.org/10.5467/JKESS.2022.43.1.60