TITLE:
AQUA Satellite Data and Imputation of Geopotential Height: A Case Study for Pakistan
AUTHORS:
Usman Saleem, Mian Sohail Akram, Muhammad Fahad Ullah, Faisal Rehman, Muhammad Riaz Khan
KEYWORDS:
AIRX3STML, Missing Data Imputations, Missing Climatic Data, Upper Air Temperature
JOURNAL NAME:
Open Journal of Geology,
Vol.8 No.10,
September
26,
2018
ABSTRACT: In current study an attempt is carried out by filling missing data of geopotiential height over Pakistan and identifying the optimum method for interpolation. In last thirteen years geopotential height values over were missing over Pakistan. These gaps are tried to be filled by interpolation Techniques. The techniques for interpolations included Bilinear interpolations [BI], Nearest Neighbor [NN], Natural [NI] and Inverse distance weighting [IDW]. These imputations were judged on the basis of performance parameters which include Root Mean Square Error [RMSE], Mean Absolute Error [MAE], Correlation Coefficient [Corr] and Coefficient of Determination [R2]. The NN and IDW interpolation Imputations were not precise and accurate. The Natural Neighbors and Bilinear interpolations immaculately fitted to the data set. A good correlation was found for Natural Neighbor interpolation imputations and perfectly fit to the surface of geopotential height. The root mean square error [maximum and minimum] values were ranges from ±5.10 to ±2.28 m respectively. However mean absolute error was near to 1. The validation of imputation revealed that NN interpolation produced more accurate results than BI. It can be concluded that Natural Interpolation was the best suited interpolation technique for filling missing data sets from AQUA satellite for geopotential height.