Analog ensemble (AE) systems for real time quantitative precipitation forecasts (QPFs) for different forecast lead times at local scale over the north-west Himalaya (NWH), India

Abstract

Heavy snowfall during winter period (November to April) over the north-west Himalaya (NWH) generates many natural hazards. Time critical decisions primarily dependent on precipitation amount such as avalanche forecasting, flood forecasting, management of necessary services and supplies etc. demand real time weather forecasts, specially, quantitative precipitation forecasts (QPFs), at local scale during winter over the NWH. Two analog ensemble systems (AE1 system, AE2 system) for QPFs for varied forecast lead times are developed utilizing surface meteorological observations of 10 stations over the NWH. Performances of developed analog ensemble systems are evaluated and compared with performances of the climatological forecast models (CM1 model, CM2 model) for same forecast lead times for binary weather forecasts (precipitation day/no precipitation day) and QPFs at 10 stations over the NWH. The AE1 (AE2) system is found to perform better as compared to the CM1 (CM2) model for binary weather forecasts and QPFs at local scale over the NWH. Performance of the AE1 system for binary weather forecasts for shorter forecast lead times 0–15 h (0–15 h), 15–24 h, 24–39 h is found comparable to performance of the AE2 system for binary weather forecasts for longer forecast lead times 0–24 h, 24–48 h, 48–72 h. However, the Mean Absolute Errors (MAEs) and Root Mean Square Errors (RMSEs) for QPFs for shorter forecast lead times with the help of the AE1 system are found less as compared to the MAEs (RMSEs) for QPFs with the help of the AE2 system for longer forecast lead times. The AE1 system can provide real time QPFs based on recent surface meteorological observations for shorter lead times which can help in dynamic decision making for weather and avalanche forecasting over the NWH. However, QPFs with the help of the AE2 system can be useful for longer forecast lead times. Performances of the AE2 system and CM2 model are evaluated for binary weather forecasts and QPFs for a week period (7 days). The AE2 system is found to perform better as compared to the CM2 model for binary weather forecasts and QPFs for a week at local scale over the NWH. These results suggest that the AE2 system exhibits better consistency for QPFs as compared to the CM2 model for a week. The MAEs (RMSEs) for QPFs with the help of the AE1(AE2) system comparable to the MAEs (RMSEs) for QPFs with the help of other forecasting methods over the NWH (or elsewhere) suggest that the AE1(AE2) system exhibits good performance for real time QPFs at local scale over the NWH.