On May 27, 2008, China successfully launched a remarkable satellite that would forever change how scientists observe our planet.
The Fengyun-3 (FY-3) series represents China's second generation of polar-orbiting meteorological satellites, succeeding the earlier FY-1 series. FY-3A, as the pathfinder of this new generation, was designed as a research and development satellite with dramatically enhanced capabilities compared to previous Chinese meteorological satellites 1 .
FY-3A operates in a sun-synchronous near-circular orbit at an average altitude of 836.4 km with an inclination of 98.75° 2 . The satellite completes each orbit in approximately 101 minutes, crossing the equator at around 10:00 AM local solar time during its southward descent 4 .
FY-3A represented a dramatic improvement over earlier Chinese meteorological satellites through several key advancements:
For the first time, FY-3A could create detailed three-dimensional profiles of atmospheric temperature and humidity 2 .
Unlike optical sensors, FY-3A's microwave instruments could see through cloud cover, enabling observation under all conditions 3 .
The satellite's imaging capabilities improved significantly, with spatial resolution ranging from 1 km to 250 m 2 .
The satellite reduced global data acquisition time from approximately one day to just two to three hours 2 .
Instruments onboard
Faster global coverage
Higher spatial resolution
All-weather capability
The diverse suite of instruments enabled FY-3A to collect a comprehensive set of environmental data, making it truly multifunctional 2 . Initially intended as an experimental mission with a reduced sensor complement, FY-3A was eventually equipped with the full sensor complement of twelve instruments, making it comparable to advanced international meteorological satellites 2 .
| Instrument | Full Name | Primary Function |
|---|---|---|
| MERSI | Medium-Resolution Spectral Imager | High-resolution imagery of land, ocean, and atmosphere |
| MWHS | Microwave Humidity Sounder | Atmospheric humidity profiling |
| MWTS | Microwave Temperature Sounder | Atmospheric temperature profiling |
| VIRR | Visible and Infrared Radiometer | Multi-spectral imaging across visible and IR spectra |
| IRAS | Infrared Atmospheric Sounder | Infrared atmospheric sounding |
| TOU/SBUS | Total Ozone Unit/Solar Backscatter Ultraviolet Sounder | Ozone layer monitoring and measurement |
| ERM | Earth Radiation Measurement | Earth's radiation budget monitoring |
| SEM | Space Environment Monitor | Space environment observations |
One particularly innovative application of FY-3A data has been in measuring and analyzing precipitable water vapor (PWV) - the total atmospheric water vapor contained in a vertical column of air. Understanding PWV is crucial for weather forecasting, climate monitoring, and hydrological cycle studies.
Traditional PWV monitoring technologies, such as water vapor radiometers and radiosondes, have limitations in temporal-spatial resolution, making it difficult to accurately capture variations and distribution patterns of atmospheric moisture 4 .
While GNSS (Global Navigation Satellite System) meteorology can provide high time resolution PWV data, its spatial resolution remains relatively low 4 .
FY-3A's MERSI instrument offered a potential solution with its five near-infrared channels specifically designed for atmospheric water vapor observation. However, the MERSI PWV product had inherent defects including cloud-contaminated data, poor accuracy, and incomplete data coverage - with studies showing its Root Mean Square (RMS) error reached 15.5 mm compared to GNSS-derived PWV 4 .
Researchers developed an innovative approach to overcome these limitations using machine learning technology 4 . The methodology included these key steps:
The experiment demonstrated remarkable success, with the reconstruction model achieving an RMS of just 0.59 mm - a dramatic improvement over the original 15.5 mm error 4 .
Original PWV Error
Reconstructed PWV Error
Accuracy Improvement
This methodology proved particularly valuable in the Three-River Headwaters region - the origin of China's major river systems - where understanding hydrological processes is crucial for water resource management 4 .
The assimilation of FY-3A data into numerical weather prediction models has revolutionized forecasting capabilities, particularly through advanced methods like the POD-4DEnVar (Proper Orthogonal Decomposition-based ensemble four-dimensional variational assimilation) technique .
The process involves mathematically integrating satellite observations with traditional weather models to create more accurate initial conditions for forecasts. The POD-4DEnVar method specifically:
Experiments assimilating FY-3A microwave temperature and humidity sounder data showed:
| System Parameter | Optimal Configuration | Impact on Assimilation Performance |
|---|---|---|
| Truncated Eigenvalues | >80% | Strong assimilation skill achieved above this threshold |
| Ensemble Members | Moderate number sufficient | Increasing physical ensemble members improves results more than initial members |
| Time Window Length | 3-5 hours | Optimal balance between data coverage and computational efficiency |
| Horizontal Localization Scale | 500 km or above | Appropriate spatial correlation range for synoptic-scale systems |
Though FY-3A was officially decommissioned in 2018 2 , its legacy continues through:
FY-3A Launch - First of China's second-generation polar-orbiting meteorological satellites
FY-3B Launch - Second satellite in the series with enhanced capabilities
FY-3C Launch - Continued the mission with improved instruments
FY-3D Launch - Advanced satellite with next-generation sensors
FY-3E Launch - First of the FY-3 series to operate in early morning orbit
Future Launches - Additional satellites (FY-3F, FY-3G, FY-3H, FY-3I, and FY-3J) scheduled 2
FY-3A represents a cornerstone in Earth observation history, marking China's transition to advanced meteorological monitoring from space. Through its diverse instrument suite and innovative applications - from water vapor reconstruction to advanced data assimilation - this remarkable satellite has contributed significantly to our understanding of Earth's complex systems. The technological advances demonstrated by FY-3A continue to influence the design and application of subsequent Earth observation missions, ensuring that we can better monitor, understand, and respond to the dynamic planet we call home. As we face growing challenges from climate change and extreme weather, the legacy of FY-3A reminds us of the invaluable role that satellite observations play in building a more resilient future.