Fog can reduce horizontal visibility below 1 km and create substantial hazards for transportation, aviation, port operations and maritime traffic. Yet monitoring its three-dimensional structure remains difficult. Ground instruments such as optical visibility meters and fog droplet spectrometers can provide accurate point measurements, but they do not map the horizontal or vertical distribution of fog. Active laser instruments can profile the atmosphere, although their signals may be severely attenuated in dense fog. Passive satellite imagers offer broad coverage but have limited vertical resolution and can struggle to distinguish fog from low cloud. Millimeter-wave cloud radar can penetrate fog, detect small hydrometeors and provide fine spatial and temporal resolution, making it a promising tool for resolving fog structure.

The research was conducted at the Datan Observation Base in Xiang’an District, Xiamen, using a YLUKA2 solid-state Ka-band dual-polarization cloud radar, a DNQ3 forward-scattering visibility meter and an FM-120 fog droplet spectrometer. The radar operated at 34.50–35.50 GHz, with a nominal spatial resolution of 30 m and a maximum detection range of 30 km. Its antenna was installed about 25 m above ground, and it performed continuous sector scans between 60 and 300 degrees at a 2-degree elevation angle. Clear-sky observations were used to characterize and subtract ground clutter, although residual contamination remained a limitation for near-range retrievals. The DNQ3, positioned approximately 153 m from the radar along a 150-degree azimuth, measured near-surface visibility using infrared pulses with a central wavelength of 0.87 micrometers.

The FM-120 supplied the droplet observations needed to constrain the retrieval. From 2019 through 2023, it measured droplets from 2 to 50 micrometers in 30 non-equidistant size bins at 1 Hz. After quality control, the development dataset contained 236,037 contributing one-second records aggregated into 4,234 valid one-minute spectra from 28 fog events. Each spectrum was classified as narrow unimodal, broad unimodal, shoulder, bimodal or uncertain. Shoulder spectra formed the largest group at 41.83%, followed by broad-unimodal spectra at 33.54%. Bimodal spectra accounted for 6.38% overall, but their prevalence increased as visibility declined: they represented 4.22% in dense fog with visibility of 200–500 m and 24.07% in very dense fog with visibility of 100–200 m. The 50–100 m interval had an estimated bimodal fraction of 35.90%, but only three events contributed to that interval, so the authors did not use it for robust quantitative inference.

These changing droplet-size distributions demonstrated why a single radar reflectivity value cannot be converted directly and uniquely into visibility. For fog droplets observed in the millimeter-wave band, radar reflectivity is proportional to the sixth moment of the droplet-size distribution, while visible-light extinction depends on the second moment and the size-dependent Mie extinction efficiency. Liquid water content is related to the third moment, and effective radius combines the second and third moments. Mathematical moment relations can connect reflectivity, liquid water content and radius, but they cannot determine both liquid water content and geometric median radius from a single-frequency measurement because droplet number concentration and distribution width remain unknown. The authors addressed this non-uniqueness with two observation-calibrated steps: a segment-wise mass-absorption method for liquid water content and attenuation correction, followed by an extinction-oriented power law relating geometric median radius to linear reflectivity.

For the liquid-water stage, the researchers adapted a self-consistent radiative-transfer algorithm in which one-way attenuation from fog water is proportional to liquid water content. A bounded reflective trust-region least-squares solver searched for parameters that reconstructed measured reflectivity while accounting for accumulated liquid-water attenuation. Because liquid water path can vary markedly within a fog profile, profiles were divided into independently fitted segments, generally spanning four to 10 range gates. Different starting vectors were used depending on whether the maximum reflectivity in a segment was above or below −15 dBZ. Once liquid water content had been retrieved, the accumulated attenuation could be used to correct the measured reflectivity. This stage required no auxiliary in-situ liquid-water measurement, but the study did not have independent reference measurements with which to validate that intermediate retrieval.

The radius stage was designed to reduce extinction errors that could arise from a conventional radius–reflectivity fit. For every FM-120 development row, the researchers searched candidate geometric median radii from 1.00 to 20 micrometers in increments of 0.01 micrometer. Each candidate was inserted into a moment-closure equation to find the radius whose predicted extinction most closely matched the same row’s size-dependent Mie extinction. These extinction-matching values were pseudo-targets derived from reflectivity, liquid water content and the same-source droplet spectrum, not independent observations of geometric median radius. An unweighted least-squares fit to the pseudo-targets yielded the selected power-law relation. On the development dataset, this relation had a mean absolute fractional extinction error of 9.37%, compared with 10.88% for a direct radius relation. The largest improvement occurred between −15 and 0 dBZ, where the error decreased from 12.25% to 4.96%.

Two structural assumptions limited the method. First, it approximated the extinction efficiency of visible light at 550 nm as a constant value of 2, the large-droplet asymptote rather than an exact representation across the small-droplet range sampled by the FM-120. This created a weak-reflectivity bias because predicted radii in cases below −40 dBZ were predominantly under 5 micrometers, where the actual Mie efficiency differs more strongly from 2. In that interval, the closed-form extinction was lower than the same-source FM-120 reference, with a mean signed residual of −25.32%. Because visibility is inversely proportional to extinction, this pattern tended to produce visibility overestimation. Second, the single-lognormal closure became less exact as droplet distributions became more complex, particularly below 200 m visibility. Calibrating the radius relation against extinction rather than radius absorbed part of this distribution-shape error, but it could not eliminate it.

Sensitivity calculations further showed that liquid water content exerts more influence on retrieved extinction than the estimated median radius. In the retrieval equation, a 10% increase in liquid water content raises extinction by 8.1%, whereas a 10% increase in radius lowers it by 4.1%. When both parameters were varied over multipliers from 0.50 to 2.00, the calculated relative extinction response ranged from −67.7% to +209.4%. Radius and liquid-water errors can partly compensate because the variables enter with opposite exponents. Drizzle presents a separate weakness: droplets larger than 100 micrometers can strongly raise radar reflectivity while contributing comparatively little to the median radius inferred from an FM-120 dataset limited to 50-micrometer droplets. The resulting retrieval error depends on competing effects between the mass-absorption liquid-water estimate and the radius closure, and the study did not quantify that trade-off with dedicated drizzle observations.

In a case on 2 March 2025, warm, humid southerly flow produced an advection sea fog that developed rapidly after 18:00 local standard time and reached maximum intensity around 21:00. Fog returns extended to approximately 10 km, the fog top exceeded 350 m and peak reflectivity approached 0 dBZ. At 20:29, the highest-reflectivity regions were concentrated south and southwest of the observation site, where the underlying topography and man-made structures could promote turbulence and droplet coalescence. Across 10 selected events in which DNQ3 visibility stayed below 1 km for at least 30 minutes without other precipitation, the new retrieval had a mean absolute error of 0.092 km and a relative error of 42.86%. A local FM-120 relation produced errors of 0.123 km and 50.53%, the Liu et al. relation produced 0.160 km and 85.30%, and the Gultepe et al. relation departed most strongly, with 0.533 km and 310.63%.

Those error statistics do not establish a definitive ranking of the methods. The radar sampled a volume at an altitude of roughly 30 m over the ground at the matched range, whereas the DNQ3 measured visibility about 1.5 m above ground. The instruments also relied on different scattering principles, and droplet sedimentation could improve near-surface visibility without producing a comparable change in the radar sample. DNQ3 observations helped select the events and identify the radar gate whose temporal pattern most closely matched the meter, making this a conditioned comparison of reasonable ranges and local consistency. The samples were also limited to spring warm fog at one southeastern coastal site; radiation fog, orographic fog and other climate regions were not tested. Independent in-situ liquid-water measurements, standardized hydrometeor phase observations, more completely collocated validation, dual-wavelength radar and measurements across more fog regimes were identified as necessary next steps.

Subject of Research: Physically constrained coastal fog visibility retrieval from single-frequency Ka-band cloud radar observations

Article Title: Physically constrained retrieval of fog visibility from millimeter-wavelength cloud radar observations

Article References: Li, X., Ge, J., Qiu, Y., Lv, Q., Song, W., Zhang, J., Zhang, C., Liu, B., Wang, J., Xia, H., & Zhu, Y. (2026). Physically constrained retrieval of fog visibility from millimeter-wavelength cloud radar observations. Atmospheric Measurement Techniques, 19(20), 6607-6623. https://doi.org/10.5194/amt-19-6607-2026

Image Credits: AI Generated

DOI: 10.5194/amt-19-6607-2026

Keywords: coastal fog, visibility retrieval, Ka-band radar, millimeter-wave radar, droplet size distribution, liquid water content, light extinction, remote sensing, fog microphysics, weather monitoring, Physically, constrained

MTG-LI is the first European geostationary lightning imager and is carried by the first Meteosat Third Generation Imaging satellite, launched on 13 December 2022. It observes Europe, Africa, the Middle East, the Atlantic and Indian oceans, and parts of South America using four cameras. Together, they cover about 84% of Earth’s disk as seen from geostationary orbit, extending to latitudes of 80 degrees north and south. Near the sub-satellite point at 0 degrees longitude, spatial sampling is about 4.5 km, while the field of view is divided into North, South, East and West sectors. Four MTG-LI instruments are to be deployed between 2022 and 2042.

Each camera images the Earth through a narrow 1.9-nanometre optical filter centered at 777.4 nanometres, the wavelength associated with lightning-excited neutral atomic oxygen emission. The instrument acquires 1,000 images per second with 1-millisecond exposures. A sudden rise in pixel radiance above a running-average background is initially recorded as a detected transient, but most such events are instrumental noise rather than lightning. Filters on board and on the ground remove signals caused by sensor noise, energetic particles, direct sunlight and reflections within the optics. EUMETSAT then groups adjacent transients captured in the same frame and combines groups occurring within 330 milliseconds and 16.5 km into flashes. The displayed time of a flash comes from its first group, while its position is calculated as the radiance-weighted centroid of all its groups.

The researchers evaluated MTG-LI against four lightning-location systems: Vaisala’s GLD360, the European Cooperation for Lightning Detection network, EUCLID, and the Geostationary Lightning Mappers on NOAA’s GOES-16 and GOES-19 satellites. GLD360 served as the principal reference because it covers the entire MTG-LI field of view, while EUCLID supplied a complementary assessment over Europe and the two GOES instruments tested the overlapping Atlantic and South American region. A two-system Bayesian method estimated absolute flash detection efficiency from conditional matches between each pair of systems. MTG-LI observations were first corrected for parallax and the roughly 120–150 milliseconds required for light to travel from clouds to the satellite, allowing a fair comparison with ground-based measurements.

GLD360 comparisons showed that detection efficiency was generally high and spatially uniform over most of the field of view. It exceeded 90% across Africa and ranged from 80% to 90% across much of Europe. Performance declined toward the outer edges, where satellites view cloud tops at increasingly oblique angles. Along a north–south transect extending from Africa to northern Scandinavia, efficiency fell from above 90% to about 73% at 70 degrees north, although the regional average remained 93.6%. The west-to-east transect showed a steeper decline, from about 95% near the sub-satellite longitude to around 40% at 75 degrees west, with an average of 67.6% in a region dominated by lightning over South America. The uneven east–west pattern remains unexplained, although the researchers considered differences in cloud brightness, storm size and viewing geometry as possible influences.

Daylight produced the clearest limitation. Flash detection efficiency was approximately 90–95% under low or absent illumination and reached a minimum of about 75% at local noon. Bright clouds raise the background radiance and therefore the threshold that an optical transient must exceed, allowing weaker discharges to pass unnoticed. The effect is partly moderated because the diurnal peak in lightning generally arrives at 16:00–17:00 local time, when efficiency has recovered to roughly 80–85%. A separate comparison with EUCLID produced a similar day-night cycle. Within EUCLID’s official European coverage area, the estimated absolute efficiency was 84.7%, generally agreeing with the GLD360-based map while revealing some flashes missed by MTG-LI in central Europe. The authors attributed these cases to small discharges inside optically thick clouds that produced weak cloud-top emissions.

Timing was especially strong, with MTG-LI matching lightning to within one millisecond throughout the reference period, apart from brief conversion errors between onboard time and coordinated universal time. Location accuracy depended on geography and time. Against GLD360, absolute errors were generally 10–15 km, with a full-field mean of 11.7 km; they ranged from 8.7 km at 12:00 UTC to more than 13 km at night. EUCLID-based estimates over Europe were better, varying from 7.1 to 11.6 km and declining from north to south: hourly errors ranged from 11.7 to 20.0 km in Finland but only 5.7 to 12.1 km in Spain. Errors worsened toward the edge of the field of view, where oblique viewing increases the importance of an assumed cloud-top height. Nighttime location estimates also degraded when the navigation system had fewer illuminated landmarks for image registration.

The false-flash analysis used GLD360 detections to map regions of storm activity on a 0.1-degree grid, then classified MTG-LI flashes outside those expanded regions as false. Across the entire field of view, the average flash false-alarm rate was 0.03 flash per second and rarely exceeded 0.5 flash per second. Of 902,716,484 detected flashes, 1,427,759 were classified as false, giving the reported 0.16% fraction. False detections were rare over Europe but more frequent over Africa and the tropical Atlantic. Distinct patterns in the accumulation map traced instrumental causes: parallel features over the tropics were associated with elevated readout noise in one camera, particularly over dark ocean scenes, while several elongated tracks were linked to space debris passing between the satellite and Earth. Brief increases associated with direct sunlight, solar glint and unusual observing conditions were also identified.

Comparison with NOAA’s geostationary lightning mappers produced lower values because the overlap region includes South America, where MTG-LI’s viewing geometry is less favorable and lightning is abundant. Estimated efficiency was 67.4% against GOES-16 from July 2024 to March 2025 and 56.1% against GOES-19 from April to December 2025, for a combined value of 61.8% across the full 18 months. Reversing the calculation indicated that GOES-19 detected 93.8% of MTG-LI flashes, compared with 85.8% for GOES-16, suggesting that operational configuration rather than instrument generation may explain much of the difference. The result does not show that MTG-LI was globally less effective than GOES: the lower number primarily reflects the edge of MTG-LI’s field of view and the concentration of strong South American lightning within the overlap. The comparison nevertheless helps determine how satellite flash detections can be combined without treating the two systems as interchangeable.

For weather monitoring, the results indicate particular value over Africa, where lightning activity is intense and radar coverage is sparse. MTG-LI’s estimated efficiency above 90% across much of the continent provides a consistent hemispheric view of storms across land and ocean, complementing rather than replacing ground networks. In Europe, its high sensitivity to in-cloud lightning could be combined with the precise cloud-to-ground locations supplied by EUCLID. Important limits remain: the efficiency figures are upper bounds because weak flashes may escape every instrument, cloud-top height estimates introduce parallax errors, and the location assessment depends partly on the accuracy and assumptions of the reference networks. The study nevertheless establishes MTG-LI as a technically capable platform for tracking the development, evolution and severity of thunderstorms, with near-continuous day-night detection, millisecond timing and an exceptionally small false-flash fraction across an ocean-to-continent observing domain.

Subject of Research: Performance assessment of the Meteosat Third Generation Lightning Imager against four lightning-location systems from July 2024 to December 2025

Article Title: Meteosat Third Generation Lightning Imager detection performances

Article References: Viticchié, B., Enno, S.-E., Navia, D., Avbelj, J., & Grandell, J. (2026). Meteosat Third Generation Lightning Imager detection performances. Atmospheric Measurement Techniques, 19(20), 6625-6642. https://doi.org/10.5194/amt-19-6625-2026

Image Credits: AI Generated

DOI: 10.5194/amt-19-6625-2026

Keywords: Meteosat Third Generation, MTG-LI, lightning detection, geostationary satellite, thunderstorms, EUMETSAT, GLD360, EUCLID, GOES lightning mappers, weather monitoring, Meteosat, Third