Study of Aircraft Icing Forecasting Methods and Their Application Scenarios over Eastern China
In this study, an aircraft icing diagnosis and forecasting method is constructed and hindcast for 25 collected spring icing cases over Eastern China based on two commonly used aircraft icing diagnostic methods (hereinafter referred to as the IC index method and the TF empirical method, respectively) and ERA5 reanalysis data as the atmospheric environmental field for icing occurrence. The spatial and temporal distribution characteristics of aircraft icing accumulation occurrence over typical cities at different latitudes in China are calculated separately, and the spatial and temporal distribution of icing accumulation areas over Xinchang, Zhejiang Province in China during one case of cold air activity is simulated. Accordingly, several application scenarios for the application of methods to forecast aircraft icing accumulation are proposed. The results indicate that among the selected icing cases, the diagnosis accuracy of the IC index method and the TF empirical method is 80% and 92%, respectively. The TF empirical method takes into account the effects of aircraft flight speed and dynamic warming, and shows better correlation with ice water particle concentration and cloud cover in medium and low clouds. However, the predicted icing accumulation intensity predicted by the TF empirical method is not accurate enough without the real flight speed of the aircraft, and there are more empty forecasts above 400 hPa. In practical applications, both the IC index method and the TF empirical method can effectively identify the icing-prone pressure levels and time periods and forecast the distribution of icing accumulation intensity at high pressure levels for a given station.
Authors
- Chen Yang (ORCID: https://orcid.org/0000-0002-5577-1879)
- Weixuan Shi
- Sha Lu (ORCID: https://orcid.org/0000-0003-3987-9887)
Institutions
- Jiangnan University (CN)
- Nanjing University of Aeronautics and Astronautics (CN)
Publication Details
- Journal
- Forecasting
- Published
- 2025-09-22
- DOI
- https://doi.org/10.3390/forecast7030053
- Primary Topic
- Icing and De-icing Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Civil Aviation Administration of China
- Fundamental Research Funds for the Central Universities