High-performance computing for the simulation of dust storms

Computers, Environment and Urban Systems

Volumn 34, Issue 4, 2010, Pages 278-290

  Xie, Jibo ^a,b   Yang, Chaowei ^a   Zhou, Bin ^a   Huang, Qunying ^a  

^a GEORGE MASON UNIVERSITY   (United States)

^b CENTER FOR EARTH OBSERVATION AND DIGITAL EARTH   (China)

Author keywords

Dust simulation; Eta; High performance computing; Parallel computing; WRF NMM

Indexed keywords

ATMOSPHERIC MODEL; COMPUTING NODES; CPU CORES; DUST EVENT; DUST MODELS; DUST STORM; EXECUTION TIME; HIGH-PERFORMANCE COMPUTING; HIGH-PERFORMANCE COMPUTING CLUSTERS; HUMAN ACTIVITIES; LINUX CLUSTERS; MESSAGE PASSING INTERFACE; MODEL OUTPUTS; NATURAL HAZARD; NEW MODEL; NONHYDROSTATIC MESOSCALE MODELS; PARALLEL COMPUTING; PARALLELIZED VERSION; PARALLELIZING; SIMULATED DUST; SIMULATION MODEL; TRANSFORMATION COMPONENTS; WEATHER FORECASTING MODEL; WEATHER RESEARCH AND FORECASTING; WEB MAP SERVICES;

CLUSTER COMPUTING; COMPUTER OPERATING SYSTEMS; DUST; GEOGRAPHIC INFORMATION SYSTEMS; MESSAGE PASSING; PARALLEL ARCHITECTURES; STORMS; WEATHER FORECASTING; WORLD WIDE WEB;

COMPUTER SIMULATION;

DUST STORM; GIS; NATURAL HAZARD; NUMERICAL METHOD; PERFORMANCE ASSESSMENT; SIMULATION; SOFTWARE; WEATHER FORECASTING;

UNITED STATES;

EID: 77953538876     PISSN: 01989715     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compenvurbsys.2009.08.002     Document Type: Article

References (33)

1. Alpert P., Krichak S.O., Tsidulko M., Shafir H., Joseph J.H. A dust prediction system with TOMS initialization. Monthly Weather Review 2002, 130(9):2335-2345.
2. Anthes R.A., Warner T.T. Development of hydrodynamic models suitable for air pollution and other meso-meteorological studies. Monthly Weather Review 1978, 106:1045-1078.
3. Barnum B.H., Winstead N.S., Wesely J., Hakola A., Colarco P.R., Toon O.B., et al. Forecasting dust storms using the CARMA-dust model and MM5 weather data. Environmental Modelling and Software 2004, 19:129-140.
4. Barros S.R.M., Kauranne T. On the parallelization of global spectral weather models. Parallel Computing 1994, 20(9):1335-1356.
5. Butler H.J., Hogarth W.L., McTainsh G.H. A source-based model for describing dust concentrations during wind erosion events: An initial study. Environmental Software 1996, 11(1-3):45-52.
6. Carpenter R.L., Droegemeier K.K., Woodward P.R. Application of the Piecewise Parabolic Method (PPM) to meteorological modeling. Monthly Weather Review 1990, 118(3):586-612.
7. Casas, M., Badia, R. M., & Labarta, J. (2008). Automatic analysis of speedup of MPI applications. In Proceedings of the 22nd annual international conference on supercomputing, Island of Kos, Greece, SESSION: Performance evaluation (Vol. 2, pp. 349-358).
8. Christensen J.H. The Danish Eulerian hemispheric model - A three-dimensional air pollution model used for the Arctic. Atmospheric Environment 1997, 31:4169-4191.
9. Drake J., Foster I. Introduction to the special issue on parallel computing in climate and weather modeling. Parallel Computing 1995, 21(10):1539-1544.
10. Grell G.A., Emeis S., Stockwell W.R., Schoenemeyer T., Forkel R., Michalakes J., et al. Application of a multiscale, coupled MM5/chemistry model to the complex terrain of the VOTALP valley campaign. Atmospheric Environment 2000, 34:1435-1453.
11. Grell G.A., Peckham S.E., Schmitz R., McKeen S.A., Frost G., Skamarock W.C., et al. Fully coupled " online" chemistry within the WRF model. Atmospheric Environment 2005, 39:6957-6975.
12. Harrison S.P., Kohfeld K.E., Roelandt C., Claquin T. The role of dust in climate changes today, at the last glacial maximum and in the future. Earth-Science Reviews 2001, 54:43-80.
13. Hazra T.K. Parallel computing. IEEE Potentials 1995, 14(3):17-20.
14. Hudspeth, W., Nickovic, S., Yin, D., Chandy, B., Barbaris, B., Budge, A., et al. (2005). PHAiRS - A Public Health Decision Support System: Initial results. In 31st International symposium on remote sensing of environment, June 20-24, Saint Petersburg.
15. Janjic Z.I. A nonhydrostatic model based on a new approach. Meteorology and Atmospheric Physics 2003, 82:271-285.
16. Janjic Z., Black T., Pyle M., Rogers E., Chuang H.-Y., DiMego G. High resolution applications of the WRF NMM. Extended abstract, 21st conference on weather analysis and forecasting/17th conference on numerical weather prediction 2005, American Meteorological Society, Washington, DC, July 31 to August 5, 2005 (21 pp).
17. Kaiser J. Mounting evidence indicts fine-particle pollution. Science 2005, 307:1858-1861.
18. Lin S.-J., Atlas R., Yeh K.-S. Global weather prediction and high-end computing at NASA. Computing in Science & Engineering 2004, 6(1):29-35.
19. Mahler A.B., Thome K., Yin D., Sprigg W.A. Dust transport model validation using satellite- and ground-based methods in the southwestern United States. Proceedings of the SPIE 2006, 6299. 62990L (September 1, 2006), San Diego, CA, USA.
20. Michalakes J., Dudhia J., Gill D., Henderson T., Klemp J., Skamarock W., et al. The weather research and forecasting model: Software architecture and performance. Proceedings of the eleventh ECMWF workshop on the use of high performance computing in meteorology 2005, 156-168. World Scientific. W. Zwiefhofer, G. Mozdzynski (Eds.).
21. NCAR, MMM Division (2004). The inaugural meeting of the wrf software training and documentation team, January 26-28.
22. Nichovic, S., Kallos, G., Kakaliagou, O., & Jovic, D. (1997). Aerosol production/transport/deposition processes in the Eta model: Desert cycle simulations. In Proc. symp. on regional weather prediction on parallel computer environments, Athens, Greece (pp. 137-145) [Preprints].
23. Nichovic S., Kallos G., Papadopoulos A., Kakaliagou O. A model for prediction of desert dust cycle in the atmosphere. Journal of Geophysical Research 2001, 106(D16):18113-18129.
24. OGC (2006). OpenGIS® Web map server implementation specification. http://www.opengeospatial.org/standards/wms.
25. Rosmond T.E., Teixeira J., Peng M., Hogan T.F., Pauley R. Navy Operational Global Atmospheric Prediction System (NOGAPS): Forcing for ocean models. Oceanography 2002, 15(1):99-108.
26. Sprigg, W. A., Yin, D. (2007). Airborne dust simulations and forecast (presentation). Pima Association of Governments Forum, June 22, 2007.
27. Taylor D.A. Dust in the Wind. Environmental Health Perspectives 2002, 110(2):A80-A87.
28. Washington W.M., Weatherly J.W., Meehl G.A., Semtner A.J., Bettge T.W., Craig A.P., et al. Parallel climate model (PCM) control and transient simulations. Climate Dynamics 2000, 16(10-11):755-774.
29. Woodward P.R., Porter D.H., Anderson S.E., Edgar B.K., Puthenveetil A., Fuchs T. Parallel computation of turbulent fluid flows with the piecewise-parabolic method. Parallel Computational Fluid Dynamics 2006, 2005:93-100.
30. Yang C., Evans J., Cole M., Alameh N., Marley S., Bambacus M. The emerging concepts and applications of the spatial web portal. PE&RS 2007, 73(6):691-698.
31. Yang C., Li W., Xie J., Zhou B. Distributed geospatial information processing: Sharing earth science information to support digital Earth. International Journal of Digital Earth 2008, 1(3):259-278.
32. Yin D., Nickovic S., Barbaris B., Chandy B., Sprigg W.A. Modeling wind-blown desert dust in the southwestern United States for public health warning: A case study. Atmospheric Environment 2005, 39(33):6243-6254.
33. Yin D., Nickovic S., Sprigg W.A. The impact of using different land cover data on wind-blown desert dust modeling results in the southwestern United States. Atmospheric Environment 2007, 41:2214-2224.