Journal of Tropical Oceanography ›› 2016, Vol. 35 ›› Issue (2): 50-56.doi: 10.11978/2015037CSTR: 32234.14.2015037

• Marine Meteorology • Previous Articles     Next Articles

A method for merging multi-source global oceanic precipitation information

SUI Yuzheng1, 4, CUI Linli2, SHI Jun3, LI Shujuan5   

  1. 1. College of Architecture, Qingdao Technological University, Qingdao 266033, China; 2. Shanghai Center for Satellite Remote Sensing and Application, Shanghai 201199, China; 3. Shanghai Climate Center, Shanghai 200030, China; 4. College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China; 5. Management College, Ocean University of China, Qingdao 266100, China
  • Received:2015-03-10 Revised:2015-09-06 Online:2016-02-29 Published:2016-02-29
  • Supported by:
    Zhejiang Provincial Open Foundation of the Most Important Subjects for the First-Level Discipline of Forestry (KF201331); The National Natural Science Foundation of China (41001283); China Clean Development Mechanism (CDM) Fund Project (2012043); China Association of Marine Affairs Project (CAMAOUC201404)

Abstract: To obtain a continuous high-resolution oceanic precipitation data, eight different oceanic precipitation products, including COADS, ECMWF, NCEP, GPCP_GPI, SSM/I_EMISS, SSM/I_SCATT, TRMM_PR, and TOPEX-TMR, were merged using an optimal weighted coefficient method to produce a new merged precipitation product. The product was obtained based on the spatial-temporal characteristics of these precipitation products and the principle of data merging. The merged product was validated using actual precipitation data from nine coastal rain gauge stations and the eight products. The merged precipitation product is better than the other data sets in terms of accuracy, and can compensate for the limitation of other multi-source precipitation products, suggesting that the optimal weighted coefficient method is an important scheme for reducing information redundancy and increasing the complementation of multi-source oceanic precipitation data sets.

Key words: oceanic precipitation, multi-source data, data merging, validation