On the Characterization and Mitigation of Noise in Space-Borne Microwave Sounding Instruments
Space-borne microwave sounding instruments have become vital data sources for weather prediction and climate change studies. Among the various radiometer configurations, the total power microwave radiometer is particularly appealing for current and future operational satellites due to its superior sensitivity and simple design. However, its performance is vulnerable to degradation caused by receiver gain fluctuations, electronic 1/f noise, and other time varying receiver characteristics. For Numerical Weather Prediction (NWP) users, 1/f noise introduces inter-channel correlations, complicating the assimilation of affected observations and reducing their accuracy. Addressing this noise issue in ground data processing system is essential to enhance the utility of microwave sounding data. This paper focuses on the characterization and mitigation of noise in current and future microwave sounding instruments, with particular emphasis on the impact of 1/f noise. Various methods are applied to quantitatively characterize noise features in both frequency and time domains. Additionally, the influence of calibration parameters on 1/f noise are analyzed. Based on these findings, we propose a mitigation algorithm for reducing noise during the on-orbit calibration of microwave sounding instruments, aiming to improve the quality of retrieved data for operational use.
Authors
- James Kam (ORCID: https://orcid.org/0000-0003-0265-0501)
- Alexandra Bringer (ORCID: https://orcid.org/0000-0001-9508-8954)
- Cheng‐Hsuan Lyu
- Matthew Sammons
- James Fuentes
- Xingming Liang (ORCID: https://orcid.org/0000-0001-5641-0509)
- Ninghai Sun
- Saji Abraham
- Hu Yang (ORCID: https://orcid.org/0000-0002-5651-4225)
- Edward Kim (ORCID: https://orcid.org/0000-0002-9828-4624)
Institutions
- Goddard Space Flight Center (US)
- Wyle (United States) (US)
- Northrop Grumman (United States) (US)
- Stinger Ghaffarian Technologies (United States) (US)
- The Eden Rivers Trust (GB)
- Astrophysics Science Division (US)
- Earth System Science Interdisciplinary Center (US)
- Science Systems and Applications (United States) (US)
- University of Maryland, College Park (US)
- Morgan State University (US)
- Philadelphia University (US)
Publication Details
- Journal
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tgrs.2025.3616644
- Citations
- 2
- Primary Topic
- Speech and Audio Processing
- Type
- article
- Field-Weighted Citation Impact
- 2.97