Correction of High and Low Temperature Forecasts in Liaoning Province under the Background of Northeast Cold Vortex

The ERA5 reanalysis data and the 6-hourly ECMWF model numerical forecasts of maximum and minimum 2m temperature were utilized to perform bias correction and error analysis on the model's daily maximum and minimum temperature elements under the background of the Northeast Cold Vortex (NECV) process during the summer of 2022, using the Kalman filter method. The results indicate that there were six NECV processes from June to August in 2022, with an average duration of 3.8 days per process. The frequency of NECV occurrences was highest in June and lowest in August. Under the NECV background in the summer of 2022, the forecast accuracy of daily maximum temperature in Liaoning Province improved from 8.0 to 15.1 percentage points after correction, while the forecast accuracy of daily minimum temperature improved from 2.5 to 6.5 percentage points. The post-correction daily maximum and minimum temperature forecasts demonstrated reduced errors and enhanced accuracy relative to the original model predictions. The correction effect for daily maximum temperature was particularly notable in the central-western and northern parts of Liaoning, whereas daily minimum temperature corrections showed better efficacy in regions excluding the southern area. This demonstrates that the Kalman filter correction method can significantly enhance the quality of daily maximum and minimum temperature forecast products in Liaoning under the NECV background. Additionally, the Kalman filter method was applied to correct daily maximum and minimum temperature forecasts in Liaoning during 2022, which showed effective correction results. This demonstrates the Kalman filter method's strong applicability in the region and provides technical support for future temperature forecasting operations.