IMPLEMENTATION OF PARALLEL ALGORITHM OF THREE DIMENSIONAL VARIATIONAL DATA ASSIMILATION
Wang Yuzhu1,2, Jiang Jinrong1, Cai Changqing1,2, Chi Xuebin1, Yue Tianxiang3
1. Supercomputing Center, Computer Network Information Center, CAS, Beijing 100190, China;
2. University of the Chinese Academy of Sciences, Beijing 100049, China;
3. Institue of Geographic Science and Natural Resources Research, CAS, Beijing 100101, China
As one of the most important data assimilation methods in numerical weather predication, 3DVAR (three-dimensional variational data assimilation) can improve the quality of data predication significantly. With gradual development of scientific research and the improvement of detecting instruments and computer technology, the traditional sequential 3DVAR system can no longer meet the demand for the high resolution and high accuracy numerical forecasting due to computational capacity and memory limit. So the parallel design and implementation of 3DVAR is very essential. In the paper, a mixed domain decomposition parallel method and message communication library are applied in the 3DVAR system of the state meteorological agency. Numerical experiments show that the 3DVAR system could run with high speedup ratio and parallel efficiency.
Barker D M, Huang W, Guo Y R, Bourgeois A J and Xiao Q N. A three-dimensional variational data assimilation system for MM5: Implementation and initial results[J]. Mon. Wea. Rev., 2004, 132(4): 897-914.
Lindskog M, Salonen K, Jarvinen H and Michelson D B. Doppler radar wind data assimilation with HIRLAM 3DVAR[J]. Mon. Wea. Rev., 2004, 132(5): 1081-1092.
Derber J, Bouttier F. A reformulation of background error covariance in the ECMWF global data assimilation system[J]. Tellus, 1999, 51A: 195-221.
Zhou G Q, Li X. An oceanic data assimilation system based on a global OGCM[G]//Corpus for pre-processing system for data input of climate models, documents for national key project: studies on short-term climate prediction system in China (1996-2000). Beijing: China Meteorology Press, 2000, 393-400.
Zhu Jiang, Zhou Guangqing, Yan Changxiang, Fu Weiwei and You Xiaobao. A three-dimensional variational ocean data assimilation system: Scheme and preliminary results[J]. Science in China( D), 2006, 49(11): 1212-1222.
Isaksen L, Hamrud M. ECMWF operational forecasting on a distributed memory platform: Analysis[J]. The 7th ECMWF Workshop on the Use of Parallel Processors in Meteorology, Shinfield Park, Reading, England, 1996.