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arxiv: 2603.19153 · v3 · pith:GLGZI6V4new · submitted 2026-03-19 · 📡 eess.SP

Mobile Radio Networks and Weather Radars Dualism: Rainfall Measurement Revolution in Densely Populated Areas

Davide Tornielli Bellini , Mario Montopoli , Dario Tagliaferri , Luca Baldini , Elisa Adirosi , Sergi Duque , Laura Resteghini , Umberto Spagnolini This is my paper

Pith reviewed 2026-05-21 10:54 UTC · model grok-4.3

classification 📡 eess.SP
keywords cellular base stationsopportunistic radarrainfall remote sensingDoppler weather radarurban hydrometeorologyground clutter mitigationradar moments retrieval
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The pith

Cellular base station signals can be turned into high-resolution urban rainfall maps using weather radar processing methods.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper sets out to prove that the dense grid of existing cellular base stations in cities can serve as a distributed radar network for measuring rainfall. It adapts established Doppler radar signal processing to extract standard weather products such as reflectivity, mean velocity, and spectral width from base station transmissions. If successful, this would deliver rain data at a few meters spatially and tens of seconds temporally without new hardware. The work focuses on overcoming ground clutter from the nearly horizontal beams through filtering, showing that the cleaned results match raw observations and independent overlapping stations.

Core claim

By processing signals from cellular base stations with techniques borrowed from Doppler weather radars, typical radar moments including reflectivity factor, mean Doppler velocity, and spectral width can be retrieved. The high density of base stations in populated areas, together with steerable arrays and wide bandwidths, yields spatial resolutions on the order of a few meters and temporal resolutions of several tens of seconds, even after addressing clutter contamination from horizontal antenna orientations.

What carries the argument

Adaptation of Doppler weather radar signal processing to extract reflectivity, velocity, and spectral width moments from opportunistic cellular base station transmissions.

If this is right

  • Urban rainfall monitoring becomes possible at meter-scale detail and near-real-time updates using only existing infrastructure.
  • Telecom networks gain a secondary use for hydrometeorology without requiring new hardware installations.
  • Clutter mitigation methods developed here enable usable radar products despite low transmit power and horizontal beam geometry.
  • Overlapped fields of view from neighboring base stations provide built-in cross-validation of the retrieved moments.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • City flood-warning systems could incorporate these dense measurements to improve short-term precipitation forecasts.
  • Similar processing might extend to monitoring other weather variables such as wind or hail using the same base station network.
  • Rural deployment would face lower station density, requiring adjustments in coverage or integration with other sensors.

Load-bearing premise

Ground clutter from nearly horizontal base station beams can be sufficiently removed by processing so that the resulting radar moments match raw data and independent overlapping measurements at acceptable quality.

What would settle it

Side-by-side comparison of rain rate estimates derived from multiple base stations against colocated rain gauges or a conventional weather radar during a real urban storm event.

Figures

Figures reproduced from arXiv: 2603.19153 by Dario Tagliaferri, Davide Tornielli Bellini, Elisa Adirosi, Laura Resteghini, Luca Baldini, Mario Montopoli, Sergi Duque, Umberto Spagnolini.

Figure 1
Figure 1. Figure 1: Conceptual visualization of BS distribution reflecting the global coverage trends derived from publicly available sources and industry reports [14]–[17]. Yellow/Orange areas indicate high density (urban regions in North America, Europe, East Asia). Dark green areas show moderate coverage. Sparse regions represent limited connectivity a); Weather radar coverage at 2019 (with permission from [18]) in b). II.… view at source ↗
Figure 2
Figure 2. Figure 2 [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Representation of time frame organization a) in the typical BS-COM working mode; b) in the experimental BS-WRM. Note that in panel a), downlink (DL) and uplink (UL) time slots are depicted as separate and contiguous slots for ease of illustration, whereas in practice they interleave using a more articulated pattern following the 3GPP standard [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Block diagram of the clutter suppression algorithm used in the BS-WRM. Textured-filled boxes indicate input and output quantities, whereas those gray-shaded are the auxiliary input parameters. where: X1(m, k; s, o) = Fw {x1(m, p; s, o)} X2(m, k; s, o) = Fw {x2(m, p; s, o)} (12) denote the complex amplitude Doppler spectra of x1(m, p; s, o) and x2(m, p; o, s), respectively, through the Fw operator defined i… view at source ↗
Figure 5
Figure 5. Figure 5: Representation of differential phase definition , ϕ(m, k; o, s) (f). The initial time sequence x = xg of N ′ p samples for a single g-th beam (a) is then processed separately in Np-wide moving windows each of them spaced by a shift quantity s (b). In a single window the time series of Np samples (c) is then divided in two distinct time series x1 and x2 as in eq. (9) and (10) of staggered samples (d), (e) o… view at source ↗
Figure 7
Figure 7. Figure 7: Example of CV σ varying the offset o (a) and persistency Ψ (b) over the same rain event. Persistency (Tobs= 20min) -2 0 2 Doppler Velocity (m/s) 3 4 5 6 7 8 9 10 11 12 0 20 40 60 80 100 Persistency (Tobs = 5min) -2 0 2 Doppler Velocity (m/s) 3 4 5 6 7 8 9 10 11 12 Range (km) [PITH_FULL_IMAGE:figures/full_fig_p010_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: As in figure 7b for o = 20, but moving from 5 min to 20 min observation time. leaving that associated to clutter on lower values, as its phase dispersion is low even at larger lags o. As a consequence, the CV thresholding in (14), is expected to produce more accurate CMV . However, increments of o produces a deterioration of Doppler resolution too, leaving also some overlap between the rain-clutter classes… view at source ↗
Figure 9
Figure 9. Figure 9: Example of ground clutter filtering on raw range-Doppler power spectrum (upper-left), obtained using the CV-driven clutter map for o = 0 and o = 20 samples (upper right and bottom left, respectively), and using the persistency-driven clutter map (bottom￾right). All the quantities plotted refer to powers in dBW. White pixels are those identified as clutter with the selected approach indicated in each panel’… view at source ↗
Figure 10
Figure 10. Figure 10: Simulations of copolar back scattering cross sections (a) for a base station in weather radar mode (BS-WRM) and custom weather radar (WR). WR is assumed to work at 5.6 GHz with horizontal (h) polarization scheme whereas BS-WRM works at 4.9 GHz having a 45◦ linear slanted polarization scheme for both transmission and reception. Comparisons in terms of reflectivity factor (Z) is in b); minimum detectable re… view at source ↗
Figure 11
Figure 11. Figure 11: Simulations of radar reflectivity factor (dBZ) for typical S-, C-, X- weather radars (a,c,e) and BS system (g) and corresponding two-way path integrated attenuation (d,d,f,h) from disdrometer alone do not allow to describe the spatial structure of N(D). In the simulation, for the BS-WRM we assumed 4.9 GHz carrier frequency with a +45◦ slanted linear polarization used for transmission and reception, wherea… view at source ↗
Figure 12
Figure 12. Figure 12: PPI sectors for two Base Stations (BSs) sites (▲, ■) with the indication of beams swiped (green) in a common Cartesian grid domain. potential and the limitations of the proposed new technique. In the results that follow, the two BSs are configured to have a range resolution of 7.5 m and a number of Np samples processed per-beam equal to 128. The beam elevation angles are fixed so that there is a tilt offs… view at source ↗
Figure 13
Figure 13. Figure 13: Example of PPIs of acquired reflectivity factor, Z, (rain+GC) for an event occurred during the experimental filed campaign (a,b) for the two BS sites as in figure 12 at identical timestamps. Identified GC is in panels (a,b) while rain only after GC filter is in (e,f). All reflectivity values are in dBZ. Left column (a,d,e) refer to BS site 1 (■), while right column (b,d,f) refer to BS site 2 (▲). The comm… view at source ↗
Figure 14
Figure 14. Figure 14: As in figure 13 but for a different timestamp and in terms of GC-filtered PPIs of Reflectivity (top), mean Doppler velocity (middle) and Doppler velocity spread (bottom) [PITH_FULL_IMAGE:figures/full_fig_p016_14.png] view at source ↗
Figure 15
Figure 15. Figure 15: Time-range reflectivity factor profiles acquired by different BS sites 1 (a) and 2 (b) along collinear beams (pink region in figure 12). The median rain rates extracted for each range profiles at the available timestamps for BS site 1 (blue) and 2 (red) is in c). ± standard deviation confidence interval is indicated by the colored bars. networked BS could help to alleviate such issue in the future. As a f… view at source ↗
read the original abstract

This study demonstrates, for the first time, how a network of cellular base stations (BSs) - the infrastructure of mobile radio networks - can be used as a distributed opportunistic radar for rainfall remote sensing. By adapting signal-processing techniques traditionally employed in Doppler weather radar systems, we demonstrate that BS signals can be used to retrieve typical weather radar products, including reflectivity factor, mean Doppler velocity, and spectral width. Due to the high spatial density of BS infrastructure in urban environments, combined with intrinsic technical features such as electronically steerable antenna arrays and wide receiver bandwidths, the proposed approach achieves unprecedented spatial and temporal resolutions, on the order of a few meters and several tens of seconds, respectively. Despite limitations related to low transmitted power, limited antenna gain, and other system constraints, a major challenge arises from ground clutter contamination, which is exacerbated by the nearly horizontal orientation of BS antenna beams. This work provides a thorough assessment of clutter impact and demonstrates that, through appropriate processing, the resulting clutter-filtered radar moments reach a satisfactory level of quality when compared with raw observations and with measurements from independent BSs with overlapped field-of-views. The findings highlight a transformative opportunity for urban hydrometeorology: leveraging existing telecommunications infrastructure to obtain rainfall information with a level of spatial granularity and temporal immediacy like never before.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript proposes using networks of cellular base stations (BSs) as a distributed opportunistic radar for rainfall remote sensing in urban areas. By adapting Doppler weather radar signal-processing techniques to BS signals, the authors claim to retrieve standard radar products including reflectivity factor, mean Doppler velocity, and spectral width. The approach exploits the high density of BS infrastructure to achieve spatial resolutions of a few meters and temporal resolutions of tens of seconds. A central focus is mitigation of severe ground clutter arising from nearly horizontal BS antenna beams; the abstract states that clutter-filtered moments achieve satisfactory quality when compared with raw observations and with independent BSs having overlapping fields of view.

Significance. If the retrievals can be shown to be quantitatively accurate against external references, the work would offer substantial significance for urban hydrometeorology by repurposing existing telecommunications infrastructure for dense, high-resolution rainfall monitoring without dedicated radar hardware. The opportunistic use of communication waveforms and electronically steerable arrays is a novel extension of established radar methods, and the emphasis on clutter mitigation addresses a key practical barrier. The current lack of numerical error metrics against calibrated references, however, prevents a full evaluation of whether the claimed products meet the accuracy needed for operational rainfall applications.

major comments (2)
  1. [Abstract] Abstract: The statement that 'clutter-filtered radar moments reach a satisfactory level of quality' is load-bearing for the central claim yet is supported only by qualitative comparison to raw observations and overlapping BSs. No quantitative metrics (bias, RMSE, correlation, or skill scores) are reported against independent references such as disdrometers, rain gauges, or co-located calibrated weather radars; internal consistency between BSs does not exclude common-mode residual clutter or waveform-induced biases.
  2. [Methods] Methods section (implied by abstract description): The adaptation of Doppler processing to low-power, limited-gain BS signals requires explicit justification of how the radar equation for reflectivity factor is modified for communication waveforms and how ground-clutter filters are tuned for near-horizontal beams; without these details or sensitivity tests, it is unclear whether the retrieved moments are physically calibrated or merely internally consistent.
minor comments (2)
  1. [Abstract] Abstract: The phrase 'unprecedented spatial and temporal resolutions' should be accompanied by a brief comparison to the resolution of existing urban rain-gauge networks or commercial X-band radars to substantiate the claim.
  2. [Title] Title: 'Dualism' is an unusual term in this context; consider replacing it with 'Integration' or 'Synergy' for clarity.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the detailed and constructive review of our manuscript. We have addressed each major comment below and revised the manuscript to improve clarity, moderate claims where appropriate, and expand methodological justifications.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The statement that 'clutter-filtered radar moments reach a satisfactory level of quality' is load-bearing for the central claim yet is supported only by qualitative comparison to raw observations and overlapping BSs. No quantitative metrics (bias, RMSE, correlation, or skill scores) are reported against independent references such as disdrometers, rain gauges, or co-located calibrated weather radars; internal consistency between BSs does not exclude common-mode residual clutter or waveform-induced biases.

    Authors: We agree that external quantitative validation against calibrated references would strengthen the central claim. The present study emphasizes feasibility and demonstrates improvements via direct comparison of raw versus processed moments and cross-consistency between independent BSs with overlapping fields of view. These internal checks provide evidence against gross residual clutter but, as the referee notes, cannot fully exclude common-mode effects. We have revised the abstract to replace 'satisfactory level of quality' with 'promising improvements in quality' and added a dedicated limitations paragraph in the Discussion that explicitly calls for future campaigns with rain gauges and disdrometers. No new external datasets were available for the current submission. revision: partial

  2. Referee: [Methods] Methods section (implied by abstract description): The adaptation of Doppler processing to low-power, limited-gain BS signals requires explicit justification of how the radar equation for reflectivity factor is modified for communication waveforms and how ground-clutter filters are tuned for near-horizontal beams; without these details or sensitivity tests, it is unclear whether the retrieved moments are physically calibrated or merely internally consistent.

    Authors: The full manuscript contains a Methods section that derives the reflectivity factor from the BS radar equation, explicitly incorporating the lower transmit power, limited antenna gain, and communication waveform properties (including bandwidth and pulse characteristics). Ground-clutter filtering is described with adaptations of established Doppler techniques tuned for near-horizontal beams, including specific filter parameters and examples of before/after spectra. We have expanded this section with additional derivation steps, a table of filter parameters, and sensitivity tests to different beam elevations and clutter strengths, clarifying the physical basis of the calibration. revision: yes

Circularity Check

0 steps flagged

No circularity: experimental demonstration rests on external cross-comparisons rather than self-referential definitions or fits.

full rationale

The paper adapts established Doppler weather-radar signal-processing methods to base-station signals and validates the resulting reflectivity, velocity, and spectral-width moments through direct comparison against raw observations and independent overlapping BSs. No equations, parameters, or claims reduce by construction to quantities defined or fitted within the same work; the clutter-mitigation assessment is presented as an empirical outcome rather than a self-fulfilling prediction. The derivation chain therefore remains self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The abstract supplies insufficient technical detail to enumerate free parameters or axioms exhaustively; the central claim implicitly rests on standard assumptions about electromagnetic propagation in rain and the effectiveness of clutter-filtering algorithms whose exact form is not specified.

axioms (2)
  • domain assumption BS signals propagate and scatter from hydrometeors in a manner sufficiently similar to dedicated weather-radar pulses to allow direct transfer of Doppler processing techniques.
    Invoked when the abstract states that BS signals can be used to retrieve reflectivity, velocity, and spectral width by adapting weather-radar methods.
  • domain assumption Ground clutter from horizontal BS beams can be adequately suppressed without destroying the meteorological signal.
    Central to the claim that clutter-filtered moments reach satisfactory quality.

pith-pipeline@v0.9.0 · 5798 in / 1542 out tokens · 33369 ms · 2026-05-21T10:54:58.627951+00:00 · methodology

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Reference graph

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