The implementation of weather modification operations involves the advance planning and deployment of equipment and personnel. If the direction of the weather system and the nature of the cloud formations can be accurately forecasted one week in advance, it plays a significant and meaningful role in the allocation of field operation resources. Supercooled water clouds are the primary targets for weather modification operations such as rain enhancement, rain suppression, and hail suppression. The formation of supercooled water depends on specific environmental conditions, including temperature, humidity, and vertical motion. To support operational forecasting for weather modification, it is necessary to accurately characterise supercooled water and its environmental fields at least one week in advance. Using the temperature and humidity forecast parameters from the CMA-GFS global model, the cloud-top temperatures for different cloud layers are calculated. The CIP (Crystal Icing Potential) algorithm is improved into a supercooled water content potential algorithm. By establishing a relational function between SLW (Supercooled Liquid Water) content and key parameters including temperature, relative humidity, and cloud-top temperature, this enhanced algorithm enables effective identification of SLW potential conducive to precipitation enhancement. A cold cloud seeding potential forecast product with a 168-hour forecast period is developed. The supercooled water potential algorithm is evaluated using both the binary classification method for icing events and the probability of detection (POD) method, incorporating 91 aircraft icing observations. Additionally, the cold-cloud seeding potential forecast results for spring 2024 are validated against 10 weather modification aircraft observations. The results show that the supercooled water potential algorithm effectively represents the likelihood of supercooled water occurrence. Validation of the supercooled water potential algorithm is conducted using 91 aircraft observation cases. When applying a 100% threshold, the icing detection rate reaches 54.5%. The icing detection rate is 97.7% and the no-icing detection rate is 66.0% when using a 15% threshold. The TSS score is 0.74 when the threshold is 25%. The cold cloud seeding potential forecast product is applied during the spring 2024 weather modification operations for rain enhancement. Out of 8 flight cases involving icing, the forecast accuracy is 87.5%, and both the 2 flight cases without icing are accurately predicted. The predictable forecast time ranges between 60 to 168 hours, and the potential reflects the intensity of icing and supercooled water, showing certain advantages over quantitative supercooled water forecasts. This product provides technical support for the process forecasting and operational outlook of weather modification activities up to one week in advance.