Scientific Research and Essays

  • Abbreviation: Sci. Res. Essays
  • Language: English
  • ISSN: 1992-2248
  • DOI: 10.5897/SRE
  • Start Year: 2006
  • Published Articles: 2758

Full Length Research Paper

Categorical statistical approach to satellite retrieved rainfall data analysis in Nigeria

Semire Folasade Abiola1,2, Rosmiwati Mohd-Mokhtar1*, Widad Ismail1, Norizah Mohamad1, and J. S. Mandeep3
1School of Electrical and Electronic Engineering, Universiti  Sains Malaysia, Engineering Campus, 14300, Nibong Tebal, Pulau Pinang, Malaysia. 2Department of Electronic and Electrical Engineering, Ladoke Akintola University of Technology, P.M.B 4000, Ogbomoso, Nigeria. 3Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia.
Email: [email protected]

  •  Accepted: 06 August 2013
  •  Published: 18 November 2013


This paperwork describes a comprehensive statistical assessment of rain gauge and satellite- based monthly and annual rainfall measurements over Nigeria during the period of 2001 to 2010. Two statistical methods were empolyed for inter-comparison and validation of the Tropical Rainfall Measuring Mission - TRMM 3B43 V7 rainfall product. TRMM was selected because of the recently developed algorithms to estimate 3D rain distribution from the visual spectrum radiance, radar and microwave sensors. The results of the continuous statistical assessment of the rainfall algorithms show good agreement with rain gauge measurement in term of correlation coefficient and improved mean error tests. The geometric mean of correlation coefficient from all the locations for annual, monthly, wet and dry period are 0.43, 0.79, 0.64, and 0.41 respectively. The categorical analysis assessment is based on the International Telecommunication Union for Radio-communication (ITU-R) recommended threshold for radio propagation. The results of Accuracy and FBI for ITU-R recommendation threshold of 1 to 10% percentage error for radio propagation applications are 0.629 and 0.901 for annual while that of monthly are 0.558 and 0.416. The overall performance of the TRMM based rainfall assessment is encouraging but more improvement is still needed for accurate and sufficient global rainfall estimation.

Key words: TRMM 3B43 V6, satellite data, cross-validation, categorical statistics, radio propagation, ITU-R.