THE RADIO FREQUENCY PROCESSING UNIT OF THE COPERNICUS IMAGING MICROWAVE RADIOMETER: AN UPDATE
Marzo 25, 2026TROPICS MICROWAVE RADIOMETER CALIBRATION ANOMALY IDENTIFICATION AND CORRECTION FOR THE NASA GLOBAL PRECIPITATION MISSION
Marzo 25, 2026H. Holbach1,2,3, Z. Jelenak4,5, S. Alsweiss6,5, S. Soisuvarn4,5, C. Shoup6, J. Sapp6, P. Chang5
1FSU, 2Northergn Gulf Institute, 3NOAA/AOML/HRD, 4UCAR, 5NOAA/NESDIS/STAR, 6GTSC
The Stepped-Frequency Microwave Radiometer (SFMR) is a critical airborne remote sensing instrument used to measure surface winds and rain rate in tropical cyclones. The quality and reliability of SFMR data are paramount for accurate hurricane intensity and structure analysis. However, real-time monitoring of the instrument’s performance and data quality remains a significant challenge. This abstract proposes the development of a new, comprehensive monitoring tool designed to address this challenge by providing live, in-situ diagnostics of SFMR instrument health and data integrity.
The motivation for this tool arose from operational challenges during a recent flight campaign, where subtle instrument anomalies were not discovered in real-time. The lack of a comprehensive monitoring system made it difficult to assess the full extent of these issues, which could have compromised the integrity of the collected data. This incident highlights the critical need for an automated, real-time diagnostic system to ensure data quality and reliability during future missions. Our proposed tool will continuously process the raw SFMR data stream, providing real-time visualization of key instrument parameters such as receiver temperature, noise levels, and calibration status. It will also incorporate algorithms to detect anomalies and flag potential issues, offering immediate alerts to operators.
The system will be designed with a simple, intuitive user interface to ensure that operators can quickly assess the instrument’s status without extensive training. By generating detailed logs and reports, the tool will also facilitate post-flight analysis and long-term trend monitoring of instrument performance. Additionally, the tool will be utilized on the SFMR historical database to detect flights from which data was compromised and that shouldn’t be used in any research studies. The ability to provide these insights in real-time represents a significant enhancement to SFMR operations, moving from reactive troubleshooting to proactive health monitoring.
In conclusion, the proposed monitoring tool aims to provide a robust, real-time solution for ensuring the operational health and data integrity of the SFMR instrument. Its future deployment is expected to improve the reliability of hurricane reconnaissance data, and ultimately contribute to more accurate forecasts by preventing the types of data issues encountered in the past.
