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Missing Data Imputations for Upper Air Temperature at 24 Standard Pressure Levels over Pakistan Collected from aqua satellite

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Journal of Data Analysis and Information Processing 2016年第3期4卷 132-146页

作者： Muhammad Usman Saleem Sajid Rashid Ahmed Institute of Geology University of the Punjab Lahore Pakistan Collage of Earth and Environmental Sciences University of the Punjab Lahore Pakistan Center for Geographic Information System Punjab University Collage of Information Technology Lahore Pakistan

This research was an effort to select best imputation method for missing upper air temperature data over 24 standard pressure levels. We have implemented four imputation techniques like inverse distance weighting, Bilinear, Natural and Nearest interpolation for missing data imputations. Performance indicators for these techniques were the root mean square error (RMSE), absolute mean error (AME), correlation coefficient and coefficient of determination ( R2 ) adopted in this research. We randomly make 30% of total samples (total samples was 324) predictable from 70% remaining data. Although four interpolation methods seem good (producing 0.99) found between actual and predicted air temperature data through this method. The high value of the coefficient of determination (0.99) through bilinear interpolation method, tells us best fit to the surface. We have also found similar results for imputation with natural interpolation method in this research, but after investigating scatter plots over each month, imputations with this method seem to little obtuse in certain months than bilinear method.

关键词： Missing Data Imputations Spatial Interpolation aqua satellite Upper Level Air Temperature AIRX3STML

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Identifying Sky Conditions in Iran from MODIS Terra and aqua Cloud Products

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Chinese Geographical Science 2017年第5期27卷 800-809页

作者： khodakaram hatami bahmanbeiglou saeed movahedi Faculty of Geographical Sciences and Planning University of lsfahanIsfahan 81746-73441Iran

Clouds can influence climate through many complex interactions within the hydrological cycle. Due to the important effects of cloud cover on climate, it is essential to study its variability over certain geographical areas. This study provides a spatial and temporal distribution of sky conditions, cloudy, partly cloudy, and clear days, in Iran. Cloud fraction parameters were calculated based on the cloud product （collection 6_L2） obtained from the Moderate Resolution Imaging Spectroradiorneter （MODIS） sensors on board the Terra （MOD06） and aqua （MYD06） satellites. The cloud products were collected daily from January 1, 2003 to December 31, 2014 （12 years） with a spatial resolution of 5 km × 5 km. First, the cloud fraction data were converted into a regular geographic coordinate network over Iran. Then, the estimations from both sensors were analyzed. Results revealed that the maximum annual frequency of cloudy days occurs along the southern shores of the Caspian Sea, while the minimum annual frequency occurs in southeast Iran. On average, the annual number of cloudy and clear-sky days was 88 and 256 d from MODIS Terra, as compared to 96 and 244 d from MODIS aqua. Generally, cloudy and partly cloudy days decrease from north to south, and MODIS aqua overestimates the cloudy and partly cloudy days compared to MODIS Terra.

关键词： cloud fraction sky conditions Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite aqua satellite Iran

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