| Parallel Computing of a Variational Data Assimilation Model for GPS／MET Observation Using the Ray-Tracing Method |
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| 作者姓名： | ZHANG Xin LIU Yuewei WANG Bin JI Zhongzhen |
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| 作者单位： | [1]KeyLaboratoryofPureandAppliedMathematics.CenterforComputationalScienceandEngineering,SchoolofMathematicalSciences,PekingUniversity,Beijing100871 [2]NationalMeteorologicalCenter,Beijing100081 [3]StateKeyLaboratoryofNumericalModelingforAtmosphericsSciencesandGeophysicalFluidDynamics,InstituteofAtmosphericPhysics,ChineseAcademyofSciencesBe~jing100029 |
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| 基金项目： | This work was supported by the National Natural Science Foundation of China under Grant No,国家重点基础研究发展计划(973计划) |
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| 摘 要： | The Spectral Statistical Interpolation (SSI) analysis system of NCEP is used to assimilate me-teorological data from the Global Positioning Satellite System (GPS/MET) refraction angles with thevariational technique. Verified by radiosonde, including GPS/ME% observations into the analysis makesan overall improvement to the analysis variables of temperature, winds, and water vapor. However, thevariational model with the ray-tracing method is quite expensive for numerical weather prediction andclimate research. For example, about 4 000 GPS/MET refraction a;~gles need to be assimilated to producean ideal global analysis. Just one iteration of minimization will take more than 24 hours CPU time onthe NCEP‘s Cray C90 computer. Although efforts have been taken to reduce the computational cost, it isstill prohibitive for operational data assimilation. In this paper, a parallel version of the three-dimensional variational data assimilation model of GPS/MET occultation measurement suitable for massive parallelprocessors architectures is developed. The divide-and-conquer strategy is used to achieve parallelism and isimplemented by message passing. The authors present the principles for the code‘s design and examine theperformance on the state-of-the-art parallel computers in China. The results show that this parallel modelscales favorably as the number of processors is increased. With the Memory-IO technique implemented bythe author, the wall clock time per iteration used for assimilating 1420 refraction angles is reduced from45 s to 12 s using 1420 processors. This suggests that the new parallelized code has the potential to beuseful in numerical weather prediction (NWP) and climate studies.
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| 关 键 词： | 数据模型 GPS MET 观测资料 光谱 统计学 |
Parallel computing of a variational data assimilation model for GPS/MET observation using the ray-tracing method |
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| ZHANG Xin,LIU Yuewei,WANG Bin,JI Zhongzhen.Parallel computing of a variational data assimilation model for GPS/MET observation using the ray-tracing method[J].Advances in Atmospheric Sciences,2004,21(2):220-226. |
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| Authors: | ZHANG Xin LIU Yuewei WANG Bin JI Zhongzhen |
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| Institution: | Key Laboratory of Pure and Applied Mathematics,Center for Computational Science and Engineering,School of Mathematicals Scienses,Peking Universty,Beijing 100871;State Key Laboratory of Numerical Modeling for Atmospherics Sciences and eophysical Fluid Dyna;National Meteorological Center,Beijing,100081;State Key Laboratory of Numerical Modeling for Atmospherics Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics,Chinese Academy of Scienses Beijing 100029 |
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| Abstract: | The Spectral Statistical Interpolation (SSI) analysis system of NCEP is used to assimilate meteorological data from the Global Positioning Satellite System (GPS/MET) refraction angles with the variational technique. Verified by radiosonde, including GPS/MET observations into the analysis makes an overall improvement to the analysis variables of temperature, winds, and water vapor. However, the variational model with the ray-tracing method is quite expensive for numerical weather prediction and climate research. For example, about 4 000 GPS/MET refraction angles need to be assimilated to produce an ideal global analysis. Just one iteration of minimization will take more than 24 hours CPU time on the NCEP's Gray C90 computer. Although efforts have been taken to reduce the computational cost, it is still prohibitive for operational data assimilation. In this paper, a parallel version of the three-dimensional variational data assimilation model of GPS/MET occultation measurement suitable for massive parallel processors architectures is developed. The divide-and-conquer strategy is used to achieve parallelism and is implemented by message passing. The authors present the principles for the code's design and examine the performance on the state-of-the-art parallel computers in China. The results show that this parallel model scales favorably as the number of processors is increased. With the Memory-IO technique implemented by the author, the wall clock time per iteration used for assimilating 1420 refraction angles is reduced from 45 s to 12 s using 1420 processors. This suggests that the new parallelized code has the potential to be useful in numerical weather prediction (NWP) and climate studies. |
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| Keywords: | parallel computing variational data assimilation GPS/MET |
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