According to information from the station, the primary solution has been focusing on digital transformation, modernizing, and automating the observation and data transmission systems. The application of science and technology has been pivotal in shortening forecast times and improving the reliability of weather and hydrological forecasts. Amid the growing unpredictability and intensity of natural disasters under the influence of climate change, over recent years, with support from the Northern Mountainous Meteorological Station, the Northern Meteorological Station, and the Điện Biên provincial Meteorological and Hydrological Station, upgrades and installation of automation technology have been progressively carried out at rain measurement stations across the province, down to the commune level.

The data, updated in real-time (up to the minute or 10 minutes), significantly aids in making accurate, timely forecasts. The Pha Đin Weather Radar Station, from where forecasts and warnings are issued, allows forecasters to analyze, assess, and provide more precise reports. The provincial KTTV station actively learns from, accesses, and integrates advanced international forecasting models, such as GSM (Japan), GFS (USA), and IFS (European Centre for Medium-Range Weather Forecasts - ECMWF), among others. Furthermore, the station uses high-resolution satellite cloud imagery and SYNOP maps showing meteorological parameters at various levels (ground level, 850mb, 700mb, 500mb, etc.) from the National Meteorological and Hydrological Center.

For hydrological forecasting, the station utilizes multiple regression equations and ARIMA models to predict river water levels. The investment in state-of-the-art warning equipment helps lay the foundation for modern forecasting, predicting long-term and short-term climate events, which is crucial in proactively responding to natural disasters.

The provincial KTTV station has closely coordinated with the provincial Steering Committee for Disaster Prevention and Search and Rescue and media agencies to timely disseminate warnings and forecasts to the public, especially when heavy rains are expected and in high-risk areas for flash floods or landslides. The station ensures that the forecasts and warnings are "complete, timely, and reliable" in line with the direction of the National Meteorological and Hydrological Center and the Northern Meteorological Station. Forecasts are sent through email, Zalo, phone calls, SMS, and direct updates to the Steering Committee, relevant departments, and other stakeholders. All processes are standardized to ensure that information reaches the right place, at the right time, and to the right person, enabling the prompt activation of disaster response plans.

According to expert assessments, in 2025, the El Niño-Southern Oscillation (ENSO) phenomenon is expected to shift towards a neutral state between May and October, with a probability ranging from 50 to 90%. This condition is conducive to the occurrence of extreme weather patterns such as prolonged heatwaves, local heavy rains, storms, and tropical depressions. Forecasts indicate that in the 2025 rainy season, phenomena like thunderstorms, tornadoes, hail, and continuous rain will be common, with instances such as heavy rainfall on March 23-24, April 5, and May 15-21, with localized rainfall exceeding 100mm in places like Ẳng Cang (149mm) and Nà Tấu (121.8mm) on May 23.

This points to a higher likelihood of extreme weather events and unpredictable developments in the upcoming rainy season, which sets increasingly higher demands on local meteorological forecasting. In response, the station has been ramping up the use of forecasting and warning models to effectively predict heavy rainfall and flooding. This necessitates continuous learning, innovation, and professional development from the station’s staff, fostering a sense of responsibility in forecasting and warning about extreme climate events.

Each forecast is not just a result of applying science and technology but also the culmination of practical experience and dedication from the station’s staff, meteorologists, and field observers. Based on forecast and warning information, relevant sectors can proactively adapt and enhance their resilience against the increasingly harsh challenges posed by climate change.