Parallelization strategies for the GPS radio Occultation data assimilation with a nonlocal operator in the weather research and Forecasting Model

Xin Zhang, Ying Hwa Kuo, Shu Ya Chen, Xiang Yu Huang, Ling Feng Hsiao

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The nonlocal excess phase observation operator for assimilating the global positioning system (GPS) radio occultation (RO) sounding data has been proven by some research papers to produce significantly better analyses for numerical weather prediction (NWP) compared to the local refractivity observation operator. However, the high computational cost and the difficulties in parallelization associated with the nonlocal GPS RO operator deter its application in research and operationalNWPpractices. In this article, two strategies are designed and implemented in the data assimilation system for the Weather Research and Forecasting Model to demonstrate the capability of parallel assimilation of GPS RO profiles with the nonlocal excess phase observation operator. In particular, to solve the parallel load imbalance problem due to the uneven geographic distribution of the GPS RO observations, round-robin scheduling is adopted to distribute GPS RO observations among the processing cores to balance the workload. The wall clock time required to complete a five-iteration minimization on a demonstration Antarctic case with 106 GPS RO observations is reduced from more than 3.5 h with a single processing core to 2.5 min with 106 processing cores. These strategies present the possibility of application of the nonlocal GPS RO excess phase observation operator in operational data assimilation systems with a cutoff time limit.

Original languageEnglish
Pages (from-to)2008-2014
Number of pages7
JournalJournal of Atmospheric and Oceanic Technology
Volume31
Issue number9
DOIs
StatePublished - 2014

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