Fast aerosol optical depth retrieval from MODIS

Abstract

Aerosol optical depth (hearafter called AOD) is an important geophysical parameter, and its retrieval from satellite data are both data and computationally intensive. This paper presents the implementation of parallel AOD retrieval from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data, based on IBM System Cluster 1600 deployed in Chinese Meteorological Administration (CMA), with focuses on the design of parallel algorithm through Single Program Multiple Data (SPMD) model. In order to demonstrate the parallel performance of the proposed parallel implementation, experiment of parallel AOD retrieval is given, and results show that the implementation of AOD parallel computing, as a viable cost-effective method, has great scalability on clusters machines, which can obtain optimum performance at 128 processors. Meanwhile, the parallel algorithm can be operationally used in AOD retrieval in the near future, which is an important input parameter for the air quality model. © 2008 IEEE.