the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 04 Dec 2025
Systematic Assessment of the RFI Environment in Passive Microwave Bands for Earth Observation from 6 to 200 GHz
Abstract. Radio Frequency Interference (RFI) is spreading worldwide, affecting numerous Earth Observation (EO) instruments. Among these, microwave radiometers play an essential role, providing critical measurements for climate monitoring, weather forecasting, and numerous other applications. In order to plan for future satellite missions and fully exploit currently available measurements, it is crucial to study the contamination levels at bands where radiometers operate. This work presents the Earth Observation RFI Scanner (EORFIScan), an RFI detection system for EO products that combines multiple RFI detection techniques in order to reduce missed detections. This software has been used to survey several passive microwave bands from 6 GHz up to 200 GHz, including both exclusive and shared bands. Analysis and validation of this method is presented for the year 2022. The resulting RFI probability maps show significant contamination in the bands up to and including 18.7 GHz. A few brightness temperatures in the range of 350–400 K have been observed at 23.8 GHz and one at 36.5 GHz, which suggest the presence of man-made emissions. At higher frequencies, RFI contamination is not clearly visible in the analysed data. Comparisons with simulated radiances from a numerical weather prediction model are presented as a way to evaluate the RFI detection, finding that flagged observations are typically warmer than model simulations, as would be expected for RFI. It is clear from the results presented that RFI is already a concern for users at lower frequency passive microwave bands, and it is recommended that real-time monitoring systems are developed to keep an eye on the evolving threat of RFI in EO bands.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-4838', Anonymous Referee #3, 30 Jan 2026
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RC2: 'Comment on egusphere-2025-4838', Anonymous Referee #4, 27 Feb 2026
This study introduces a radio frequency interference (RFI) detection system for Earth observation products, which combines multiple RFI detection techniques to reduce missed detections. The system evaluated the RFI environment in the passive microwave frequency band for ground observation at 6-200GHz，and analysis and validation of it is presented for the year 2022. Overall, the manuscript was well written, however, some of the issues (as stated below) need to be solved/ clarified:
1. Five RFI techniques are listed in the manuscript: Intensity algorithm, Polarization ratio, Spatial Variability, Image Enhancement and Generalized RFI Index. In this paper, Polarization Ratio Method only applies to the AMSR2 instrument, and what methods are applied for other instruments respectively? Sometimes, the same method may not be suitable for all surface types.
2. P12 Line 251: “Furthermore, after discarding measurements potentially affected by sun glint, observations over 350 K were stored along with their latitude, longitude and date per each frequency band.”
P15 Line 301:“Analysis of the AMSR2 measurements at 23.8 GHz highlighted instances in which the measured brightness temperature was between 350 K and 400 K which indicates presence of RFI. Some of those observations are due to by sun glint effects, and they were discarded from the analysis.”
How to distinguish whether the observations with brightness temperature values between 350-400K are affected by RFI or sun glint effects? On a specific surface of the Earth or within a certain range of sun glint angles?
Are only those AMSR2 observations at 23.8GHz affected by sun glint? What about other frequencies or instruments?
3. Figures 5 and 6 show mean RFI probability maps for selected channels from the four instruments considered, covering the frequency range 6.9 GHz to 183 GHz.
Although the RFI signal at 23.8GHz is not as significant as other low-frequency channels (Figures 5), those observations over 350 K were grouped in clusters and are listed in the Table 3. The locations of all RFI at 23.8 GHz showed in Figures 8 does not seem to match the ones in Figure 5(e). And a similar situation exists for 36.5 GHz (Figure 6(b) & Figures 8).
4. BC term in Equation 13: Are the values of BC term different for different channels? Is the average value of BC term at different channels about 5K?
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General assessment
The manuscript addresses an important and timely problem: the impact of radio-frequency interference on passive microwave observations across a broad frequency range. The topic is clearly relevant for the Earth observation and NWP communities, and the attempt to apply a consistent framework across instruments and bands is valuable.
However, the paper sits uneasily between a methods paper and an application or survey paper. Large parts are devoted to describing the EORFIScan framework, while the results and validation resemble a collection of case studies. This mixed focus leads to ambiguity in scope and weakens the conclusions. The manuscript does not yet provide the level of methodological validation expected for a methods paper, nor the statistical robustness implied by a systematic global survey.
RFI indicators, geophysical variability, and resolution effects
A central issue concerns the specificity of the “RFI indicators” used in EORFIScan. The applied techniques, intensity thresholds, polarization ratios, spatial variability, high-pass filtering, and multi-channel regression residuals, are well established in passive microwave processing. In particular, the spatial variability and image enhancement filters are mathematically equivalent to edge-detection operators commonly used to identify coastlines, sea-ice margins, and other sharp geophysical gradients.
The manuscript itself acknowledges that many detections coincide with sea-ice edges, coastal upwelling regions, and complex terrain. While combining multiple indicators may reduce missed detections, the paper does not convincingly demonstrate that the resulting flags are specific to man-made interference rather than natural surface variability. Given that the conclusions rely heavily on spatial pattern interpretation, this ambiguity is problematic.
This concern is amplified by resolution issues. The study combines data from AMSR2, AMSU-A, MWHS-2, and AMR-C, which differ substantially in spatial resolution, scan geometry, and antenna characteristics. It is unclear whether the data are resolution-matched before applying spatial operators, or whether antenna pattern effects are treated consistently. Without resolution harmonization (e.g. Backus–Gilbert or equivalent approaches), edge-based methods are particularly prone to artefacts. Many of the strongest “RFI probability” features occur precisely in regions where such effects are expected to be largest, making it difficult to separate true RFI from instrumental or sampling artefacts.
Interpretation and validation using departures
The comparison with NWP background departures is one of the strongest elements of the paper. The swath-level examples in Figure 10 are convincing and show that many flagged observations correspond to strong, localized positive departures that are hard to explain by geophysical variability alone. These examples demonstrate that the framework can identify genuine RFI.
At the same time, this validation is limited to a single day, a restricted region, and mainly low-frequency AMSR2 channels. While illustrative, it does not support the broader claim of a systematic assessment across frequencies, instruments, and time. Aggregated statistics are presented later, but departure-based validation is not applied consistently or extensively enough to underpin the global conclusions.
The interpretation of the RFI probability maps is further hindered by the graphical presentation. In particular, the colour scales used in Figures 5 and 6 make it difficult to clearly identify contaminated areas and to compare signals across frequencies.
Validation strategy and supporting data
The use of RTTOV-SCATT NWP simulations for validation is appropriate and well established. However, quantitative validation is limited to a subset of channels and periods, while conclusions for higher frequencies rely largely on the absence of visually obvious signals. Detection limits and false alarm rates are discussed only qualitatively, and no rigorous performance metrics are provided.
The lack of ground truth is acknowledged, but this makes it especially important to demonstrate that flagged signals cannot be explained by plausible geophysical or modelling errors. In several cases, particularly near coasts, ice edges, and complex terrain, the manuscript itself attributes detections to surface effects, raising questions about the robustness of the detection framework.
The discussion of oceanic RFI would also benefit from external constraints. Although shipping and offshore infrastructure are mentioned as likely sources, no independent datasets such as AIS ship tracking are used to support these interpretations, despite their availability.
Frequency coverage and title consistency
The title and abstract emphasize a survey from 6 to 200 GHz. In practice, the most detailed analysis and validation focus on frequencies below about 20 GHz. For higher frequencies, conclusions are largely negative and not supported by comparable quantitative analysis. This mismatch weakens the narrative and makes the use of the term “systematic” in the title potentially misleading, as the validation is neither statistically nor methodologically systematic across the full frequency range.
Reproducibility and AMT data policy
Finally, the study does not meet AMT requirements for reproducibility. Although the processing steps are described, the EORFIScan implementation, thresholds, coefficients, and configuration choices are not made available. Neither code nor processed datasets are publicly accessible. For a methods-oriented paper proposing a general-purpose detection framework, this is a serious limitation, as independent reproduction and verification are not possible.