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, Bil...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 ( R<sup>2</sup> ) 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 <1 RMSE, AME) for imputations of air temperature data, but bilinear method was the most accurate with least errors for missing data imputations. RMSE for bilinear method remains <0.01 on all pressure levels except 1000 hPa where this value was 0.6. The low value of AME (<0.1) came at all pressure levels through bilinear imputations. Very strong correlation (>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.展开更多
The objective of this research is to investigate the effects of cosmic ray Forbush Decreases (FDs) exceeding 7% in magnitude, occurring between 1985 and 2016, on upper atmospheric pressure and temperature at Abha and ...The objective of this research is to investigate the effects of cosmic ray Forbush Decreases (FDs) exceeding 7% in magnitude, occurring between 1985 and 2016, on upper atmospheric pressure and temperature at Abha and Tabouk. Employing the super epoch analysis method, the study concentrated on altitudes of 5 km and 10 km, uncovering significant variations. Seasonal and synoptic-scale variations were considered and excluded when necessary across eight 9-day periods. Both locations showed considerable fluctuations in pressure and temperature before and after the events. At 5 km altitude (21 events), Abha experienced more pressure increases both before (9 vs. 7) and after (12 vs. 11) the events compared to Tabouk. For temperature, Abha recorded more increases before the events (5 vs. 1), while Tabouk showed more decreases (19 vs. 15). Post-event, Tabouk had more temperature increases (13 vs. 10). At 10 km altitude (20 events), both regions experienced more decreases than increases in pressure and temperature before the events and more increases afterward. Notably, Abha experienced more pressure increases both 4 days before (9 vs. 7) and after the events (12 vs. 11) than Tabouk. For temperature, Abha recorded more increases before the events (5 vs. 1), while Tabouk showed more decreases (19 vs. 15). Post-event, Tabouk had more temperature increases (13 vs. 10). These findings underscore both similarities and differences in atmospheric responses to FDs between Abha and Tabouk. Both locations exhibited cooling trends before and warming trends after the events, with Tabouk demonstrating a more pronounced warming trend post-event. These results enhance our understanding of the atmospheric dynamics linked to FDs and assist in predicting weather patterns associated with these phenomena.展开更多
文摘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 ( R<sup>2</sup> ) 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 <1 RMSE, AME) for imputations of air temperature data, but bilinear method was the most accurate with least errors for missing data imputations. RMSE for bilinear method remains <0.01 on all pressure levels except 1000 hPa where this value was 0.6. The low value of AME (<0.1) came at all pressure levels through bilinear imputations. Very strong correlation (>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.
文摘The objective of this research is to investigate the effects of cosmic ray Forbush Decreases (FDs) exceeding 7% in magnitude, occurring between 1985 and 2016, on upper atmospheric pressure and temperature at Abha and Tabouk. Employing the super epoch analysis method, the study concentrated on altitudes of 5 km and 10 km, uncovering significant variations. Seasonal and synoptic-scale variations were considered and excluded when necessary across eight 9-day periods. Both locations showed considerable fluctuations in pressure and temperature before and after the events. At 5 km altitude (21 events), Abha experienced more pressure increases both before (9 vs. 7) and after (12 vs. 11) the events compared to Tabouk. For temperature, Abha recorded more increases before the events (5 vs. 1), while Tabouk showed more decreases (19 vs. 15). Post-event, Tabouk had more temperature increases (13 vs. 10). At 10 km altitude (20 events), both regions experienced more decreases than increases in pressure and temperature before the events and more increases afterward. Notably, Abha experienced more pressure increases both 4 days before (9 vs. 7) and after the events (12 vs. 11) than Tabouk. For temperature, Abha recorded more increases before the events (5 vs. 1), while Tabouk showed more decreases (19 vs. 15). Post-event, Tabouk had more temperature increases (13 vs. 10). These findings underscore both similarities and differences in atmospheric responses to FDs between Abha and Tabouk. Both locations exhibited cooling trends before and warming trends after the events, with Tabouk demonstrating a more pronounced warming trend post-event. These results enhance our understanding of the atmospheric dynamics linked to FDs and assist in predicting weather patterns associated with these phenomena.
