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	<title>aviation meteorology &#8211; Science</title>
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	<title>aviation meteorology &#8211; Science</title>
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		<title>Why Winter Fog Refuses to Lift: New Study Decodes the Boundary-Layer Secrets of the Gangetic Plains</title>
		<link>https://scienmag.com/why-winter-fog-refuses-to-lift-new-study-decodes-the-boundary-layer-secrets-of-the-gangetic-plains/</link>
		
		<dc:creator><![CDATA[Russell Cooper]]></dc:creator>
		<pubDate>Fri, 09 Oct 2026 12:20:57 +0000</pubDate>
				<category><![CDATA[Earth Science]]></category>
		<category><![CDATA[alluvial basin climate]]></category>
		<category><![CDATA[atmospheric thermodynamics]]></category>
		<category><![CDATA[aviation meteorology]]></category>
		<category><![CDATA[boundary layer]]></category>
		<category><![CDATA[boundary layer dynamics]]></category>
		<category><![CDATA[boundary-layer meteorology]]></category>
		<category><![CDATA[ERA5 reanalysis]]></category>
		<category><![CDATA[fog]]></category>
		<category><![CDATA[fog case studies in India]]></category>
		<category><![CDATA[fog dissipation]]></category>
		<category><![CDATA[fog duration analysis]]></category>
		<category><![CDATA[fog formation and dissipation]]></category>
		<category><![CDATA[fog impact on transportation]]></category>
		<category><![CDATA[Gangetic Plains]]></category>
		<category><![CDATA[haze and air pollution]]></category>
		<category><![CDATA[Indo-Gangetic Plain]]></category>
		<category><![CDATA[Patna Airport]]></category>
		<category><![CDATA[radiosonde]]></category>
		<category><![CDATA[reanalysis weather data]]></category>
		<category><![CDATA[Richardson number]]></category>
		<category><![CDATA[temperature inversion]]></category>
		<category><![CDATA[ventilation coefficient]]></category>
		<category><![CDATA[western disturbances]]></category>
		<category><![CDATA[Winter fog]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=253841</guid>

					<description><![CDATA[A new case study of the December 2025 fog siege at Patna Airport shows that persistence depends on a coordinated double-lock of inversion geometry, extreme stability, and collapsed ventilation, while mechanical mixing drives most fog dissipation.]]></description>
										<content:encoded><![CDATA[<p>Every winter, a thick grey shroud descends over the Eastern Gangetic Plains of India, grounding flights, stranding trains, and turning highways into hazard zones. Now a detailed case study of a punishing two-week fog episode at Patna Airport has revealed, with unusual quantitative precision, why the region&#8217;s fog lingers for so long and what finally tears it apart. The research, published in Discover Geoscience, examined conditions between 16 and 31 December 2025, when twelve separate fog events pushed visibility below 1000 metres and, at the worst moments, down to roughly 200 metres for stretches approaching twenty hours. By combining airport surface observations, runway visual range measurements, daily radiosonde soundings, and the European Centre for Medium-Range Weather Forecasts ERA5 reanalysis, the team built one of the most complete thermodynamic portraits yet of fog life over this densely populated alluvial basin.</p>
<p>The study area itself is almost engineered for fog. The Eastern Gangetic Plain spans roughly 94,000 square kilometres of flat land lying mostly below 100 metres, wedged between the Himalayas to the north, with peaks exceeding 8000 metres, and the Chotanagpur Plateau to the south. This basin-like geometry traps moisture and aerosols, while westerly and northwesterly winds in winter funnel pollutants from western India and Pakistan into the region like a low-level atmospheric river, supplying abundant condensation nuclei. Add elevated soil moisture from irrigation and river systems, recurrent cold-wave episodes, and weak pressure gradients that keep horizontal winds sluggish, and the ingredients for persistent dense fog assemble almost automatically each December and January. At Jay Prakash Narayan International Airport in Patna, situated centrally in the basin at about 53 metres above sea level, runway visual range regularly falls below operational minima, producing cascading delays, diversions, and cancellations.</p>
<p>Two contrasting fog episodes dominated the study window, and their differences turned out to be scientifically revealing. The first, from 16 to 19 December, was synoptically forced: a deep, positively tilted upper-level trough anchored over northwest India drove strong southwesterly jet flow above 20 metres per second, cold-air advection, and a spatially coherent signature of subsidence at 700 hectopascals, with pressure velocities between minus 10 and minus 20 times ten to the minus two pascal-seconds. This descending branch of an active western disturbance reinforced a capping inversion over the fog layer. The second episode, from 23 to 27 December, unfolded after the trough moved eastward and quasi-geostrophic forcing for ascent weakened. Vertical motion over Patna became fragmented and nearly neutral, and the boundary layer shifted into a radiative-thermodynamic regime, exquisitely sensitive to the diurnal cycle, yet paradoxically more stable and longer-lived than the first.</p>
<p>The turbulence diagnostics from the second episode were extraordinary. Turbulent kinetic energy, which peaked near 60 square metres per second squared around 23 and 24 December, collapsed to nearly zero by 25 December and stayed there. Wind shear fell from about 10 times ten to the minus three per second to between 3 and 5 times the same unit. The bulk Richardson number, a dimensionless ratio weighing buoyant suppression of mixing against mechanical shear production, climbed to roughly +300 on 24 December and then held between +100 and +200 for three days, the highest sustained values in the entire record. Ventilation coefficients, the product of boundary-layer height and 10-metre wind speed, crashed from about 6000 square metres per second to 1000 to 1500, indicating the most severe atmospheric dispersion limitation observed. Mixing heights were squeezed to just 250 to 350 metres. In effect, every mechanism that could erode the fog was switched off simultaneously.</p>
<p>From the radiosonde analysis emerged what the authors call a double-lock mechanism for fog persistence. Persistent dense fog required not one condition but a coordinated set: surface-based temperature inversions with bases below roughly 150 to 200 metres, moderate thermal strengths of 2 to 6 degrees Celsius, vertical depths exceeding 2000 metres, bulk Richardson numbers above 10 to 20, and ventilation coefficients below about 5000 to 6000 square metres per second. When normalized inversion strength and depth both exceeded 0.5 alongside these stability and ventilation constraints, persistent fog reliably followed. The 2000-metre depth threshold proved especially diagnostic, separating brief events lasting under six hours from prolonged ones exceeding fifteen hours, consistent with mixed-layer theory in which deeper capping inversions resist turbulent erosion far longer than shallow ones.</p>
<p>Perhaps the most striking single observation came on 29 December, after the main episodes had ended. A powerful inversion with a thermal strength of 10.5 degrees Celsius sat with its base above 700 metres, and it produced no fog at all. The reason is geometric rather than thermodynamic: an elevated inversion decouples the stable layer from surface moisture, so however strong the temperature jump, it cannot trap water vapour where fog droplets need to condense. Inversion placement, the study concludes, matters more than inversion intensity. This finding directly challenges forecasting practice that weights inversion magnitude alone, and it underscores the primacy of surface-atmosphere coupling in continental fog formation. During the same transition, the Richardson number swung from +60 to -50 within twenty-four hours, ventilation coefficients surged to 8000 to 10000 square metres per second, and inversion strength collapsed from 10.5 to below 2 degrees Celsius, a coordinated multi-parameter disaggregation triggered by synoptic rearrangement.</p>
<p>To understand how fog actually dies, the researchers built a rule-based classification framework assigning each of 49 dissipation events to radiative, subsidence-driven, mechanical, or mixed categories, ordered by precedence from synoptic vertical motion through surface wind and shear to residual radiative signatures. The result was unambiguous: mechanically driven processes, whether acting alone or jointly with other boundary-layer dynamics, dominated fog erosion. Mixed-mechanical events accounted for 51.0 percent of cases and pure mechanical dissipation another 20.4 percent, meaning wind shear intensification and turbulent mixing governed roughly 71 percent of all fog clearance at Patna. Mixed-subsidence pathways contributed 14.3 percent, while pure radiative, pure subsidence, and mixed-radiative mechanisms together managed only about 8 percent, a reflection of winter&#8217;s short days, low solar angles, and optically thick fog layers that starve the surface of warming radiation. A small residual of 6.1 percent remained diagnostically ambiguous, clustered under extreme stability where all dissipative signals fell below detection thresholds.</p>
<p>The framework was stress-tested and verified rather than merely asserted. A sensitivity analysis perturbing each classification threshold by plus or minus 10 and 20 percent of its interquartile range showed that radiative thresholds were highly stable, with zero reclassification for several parameters, while mechanical thresholds, ironically governing the dominant category, were the least robust, reclassifying up to 39 percent of events under the largest perturbation. Binary verification of the fog-favourable criterion, a transitional inversion with base between 50 and 500 metres, against 384 matched surface observations yielded an accuracy of 0.77, precision of 0.76, recall of 0.33, an F1-score of 0.46, and a Heidke Skill Score of 0.34, confirming genuine predictive skill beyond climatology. The high-precision, low-recall profile positions the tool as a conservative, low-false-alarm mechanism-attribution instrument rather than an exhaustive all-height fog forecaster, a distinction with real operational consequences for aviation safety managers who must balance disruption costs against missed warnings.</p>
<p>The practical payoff is a companion Fog Dissipation Potential Index that distills the multi-parameter picture into short-lead operational guidance, distinguishing transient from persistent fog and clarifying where predictability simply runs out under extreme stability. The authors benchmarked their diagnostic approach against a complementary decision-tree nowcasting system developed for Delhi&#8217;s Indira Gandhi International Airport, noting that the two converge on similar wind-speed regime boundaries and could be paired operationally, since the decision tree&#8217;s known failure mode, fog onset without relative humidity saturation at tower level, is precisely the signature this framework would attribute to subsidence or mechanical forcing. The team is candid about limitations: aerosol indicators such as PM2.5 and cloud condensation nuclei were deliberately excluded, turbulent kinetic energy cannot be resolved from standard ERA5 fields, thresholds are site- and season-specific, and some moisture parameters are collinear by construction. Even so, for one of the most fog-burdened and economically vital regions on Earth, the study delivers something rare: physically interpretable, quantitatively verified thresholds that explain not just when the fog comes, but why it stays, and what finally sets the plains free.</p>
<p><strong>Subject of Research:</strong> Boundary-layer thermodynamic controls on winter fog persistence and dissipation over the Eastern Gangetic Plains</p>
<p><strong>Article Title:</strong> Fog persistence and dissipation over the Eastern Gangetic Plains insights from boundary layer thermodynamics during 16 to 31 December 2025</p>
<p><strong>Article References:</strong> Shankar, A., Kant, S., Anand, A., &amp; Sarthi, P. P. (2026). Fog persistence and dissipation over the Eastern Gangetic Plains insights from boundary layer thermodynamics during 16 to 31 December 2025. <em>Discover Geoscience, 4</em>(1), Article 307. <a href="https://doi.org/10.1007/s44288-026-00684-2" rel="noopener noreferrer">https://doi.org/10.1007/s44288-026-00684-2</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1007/s44288-026-00684-2" rel="noopener noreferrer">10.1007/s44288-026-00684-2</a></p>
<p><strong>Keywords:</strong> fog, Indo-Gangetic Plain, boundary layer, temperature inversion, Richardson number, ventilation coefficient, radiosonde, ERA5 reanalysis, aviation meteorology, fog dissipation, Patna Airport, western disturbances</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">253841</post-id>	</item>
		<item>
		<title>Istanbul&#8217;s Fog Is Far More Local Than Anyone Thought, 12-Year Study Reveals</title>
		<link>https://scienmag.com/istanbuls-fog-is-far-more-local-than-anyone-thought-12-year-study-reveals/</link>
		
		<dc:creator><![CDATA[Violet Maxwell]]></dc:creator>
		<pubDate>Thu, 01 Oct 2026 11:51:26 +0000</pubDate>
				<category><![CDATA[Earth Science]]></category>
		<category><![CDATA[advection fog]]></category>
		<category><![CDATA[aviation meteorology]]></category>
		<category><![CDATA[aviation weather analysis]]></category>
		<category><![CDATA[Black Sea influence on Istanbul weather]]></category>
		<category><![CDATA[boundary-layer meteorology]]></category>
		<category><![CDATA[city topography and fog formation]]></category>
		<category><![CDATA[coastal megacity fog dynamics]]></category>
		<category><![CDATA[fog climatology]]></category>
		<category><![CDATA[high-frequency weather observations Istanbul]]></category>
		<category><![CDATA[Istanbul]]></category>
		<category><![CDATA[Istanbul airport weather variations]]></category>
		<category><![CDATA[localized boundary-layer fog]]></category>
		<category><![CDATA[long-term climate study Istanbul]]></category>
		<category><![CDATA[low visibility]]></category>
		<category><![CDATA[METAR observations]]></category>
		<category><![CDATA[neighborhood-scale urban heat effects]]></category>
		<category><![CDATA[radiation fog]]></category>
		<category><![CDATA[regional climate variability in Istanbul]]></category>
		<category><![CDATA[satellite imagery in urban climate research]]></category>
		<category><![CDATA[Theoretical and Applied Climatology]]></category>
		<category><![CDATA[Türkiye]]></category>
		<category><![CDATA[urban fog behavior]]></category>
		<category><![CDATA[urban heat island]]></category>
		<category><![CDATA[urban microclimate]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=222466</guid>

					<description><![CDATA[A 12-year analysis of aviation observations across three Istanbul airports shows that fog in the megacity is a highly localized, winter-dominated phenomenon, with advection fog prevailing inland and radiation fog in the urban south.]]></description>
										<content:encoded><![CDATA[<p>Fog in a megacity is not one phenomenon but many, and nowhere is that clearer than in Istanbul, where a new long-term analysis has revealed just how sharply the city&#8217;s fog behavior diverges from one airport to the next. A team of researchers at Istanbul Technical University examined more than a decade of high-frequency aviation weather observations across three of the city&#8217;s airports, combining them with weather balloon profiles and satellite imagery to build the most detailed picture yet of how fog forms, persists, and vanishes across this sprawling coastal metropolis. Their findings, published in Theoretical and Applied Climatology, show that fog in Istanbul behaves as an intensely localized boundary-layer phenomenon, shaped as much by neighborhood-scale topography and urban heat as by the large-scale weather systems sweeping in from the Black Sea and the Sea of Marmara.</p>
<p>The study drew on an unusually rich observational foundation. The researchers compiled routine and special aviation weather reports issued every thirty minutes from three airports serving Istanbul: Sabiha Gökçen, identified in the study by its ICAO code LTBA, situated on the city&#8217;s Anatolian side; Istanbul Airport, coded LTFM, on the northwestern shore near the Black Sea; and Atatürk&#8217;s successor regional field LTFJ in the eastern inland part of the metropolitan area. These half-hourly reports, which record visibility, cloud base, temperature, dew point, wind, and pressure, were supplemented by radiosonde soundings that profile the vertical structure of the lower atmosphere and by microphysics satellite imagery capable of distinguishing cloud properties at night. From this combined dataset, the team applied an objective physical typing algorithm that sorts every fog event into one of five mechanistic categories: advection fog, radiation fog, precipitation fog, cloud-base lowering, and evaporation fog.</p>
<p>The classification matters because each fog type carries a distinct physical signature and a distinct forecasting challenge. Advection fog forms when moist air flows horizontally over a cooler surface, chilling the air to its dew point; it is the classic fog of coastal regions where warm, humid maritime air drifts across cold water or cold land. Radiation fog, by contrast, is born on clear, calm nights when the ground radiates heat skyward, cooling the air layer in contact with it until condensation begins. Precipitation fog arises when rain falls through drier air and evaporates, pumping moisture into the boundary layer. Cloud-base lowering describes stratus decks that descend until they effectively become fog at the surface, while evaporation fog forms when water evaporates from a warm surface into cooler air above. Sorting events into these categories allowed the researchers to trace each airport&#8217;s fog regime back to its thermodynamic roots.</p>
<p>The spatial contrasts the analysis uncovered are striking. Over the extended historical period from 2012 to 2023, the eastern inland station LTFJ logged an average of 17.2 fog days per year, more than five times the 3.2 fog days recorded annually at the southern urban station LTBA. The dominant fog mechanism also differed fundamentally between the two sites. At LTFJ, advection fog accounted for 53 percent of events, a signature of moist air being transported into the area and chilled over locally cool surfaces. At LTBA, radiation fog dominated at 55 percent, and the researchers attribute this to the interplay of urban heat island effects and topographic shielding around the airport. The urban heat island raises nighttime minimum temperatures, making it harder for the near-surface air to reach saturation, while surrounding terrain can block or channel the drainage flows and moist intrusions that feed fog elsewhere in the city.</p>
<p>When the analysis was restricted to the common period from 2019 to 2023, during which all three airports provided overlapping records, the three-way comparison sharpened the picture further. LTFJ recorded 52 fog-affected days over that window, LTBA just 12, and LTFM, the northern airport closest to the Black Sea coast, 57. Advection fog again led the statistics at both LTFJ, where it made up 50 percent of events, and LTFM, where it reached 56 percent. The elevated fog frequency at LTFM fits its coastal geography: proximity to the Black Sea supplies abundant low-level moisture, and the temperature contrasts between sea and land provide the cooling mechanism that advection fog requires. That two airports separated by a few dozen kilometers within the same metropolitan area can differ by nearly a factor of five in annual fog days underscores how strongly microclimate and siting control fog occurrence in complex coastal terrain.</p>
<p>The temporal structure of Istanbul&#8217;s fog is equally distinctive. The analysis demonstrated a pronounced winter peak, with fog activity concentrated in November and February, and a complete absence of fog during the summer months. This seasonality reflects the underlying thermodynamics. Winter brings longer nights, weaker solar heating, lower sea-surface and land-surface temperatures, and a greater supply of moist air masses moving across relatively cool waters, all of which favor the saturation of the boundary layer. Summer, with its strong insolation and warm surfaces, keeps the near-surface air well above its dew point even under maritime influence. For aviation planners and forecasters, the message is that Istanbul&#8217;s fog risk is not evenly distributed through the year but clusters sharply in the cold season, with November and February emerging as the critical months for low-visibility operations.</p>
<p>Perhaps the most consequential finding concerns spatial coherence. Between 2019 and 2023, the researchers evaluated how often fog occurred simultaneously at all three observation nodes, and the answer was remarkably small: only four days in five years saw all three airports shrouded at once. In other words, Istanbul&#8217;s fog is profoundly fragmented, appearing at one airport while the others remain clear. This localized fragmentation has direct operational implications. Flight diversions, holding patterns, and ground delays are typically triggered by visibility conditions at a single destination airport, so a fog climatology built on city-wide averages would badly misrepresent the actual risk. A pilot approaching one Istanbul facility may encounter dense fog while another facility across the city operates normally, a pattern that only station-specific, mechanism-aware forecasting can capture.</p>
<p>The study&#8217;s methodology also highlights the value of combining conventional surface observations with remote sensing. Radiosonde profiles reveal the depth and structure of the temperature inversion layers that cap and nourish radiation fog, while night microphysics satellite imagery allows researchers to track fog patches across the metropolitan area between routine observation times, confirming events that a single surface station might miss or mischaracterize. Supplementary analyses in the paper examined the distribution of fog-affected observations by cloud cover, cloud base height, runway visual range, and surface pressure, along with satellite composites of notable fog episodes in February 2019 and November 2021, building a multi-layered empirical baseline for the region.</p>
<p>Istanbul is far from alone in facing the forecasting puzzle of urban fog, and the study situates itself within a growing international literature. Comparable event-based climatologies have been constructed for New York City, Casablanca, Abu Dhabi, Cape Town, Belgrade, Lisbon, Perth, Shanghai Pudong, and airports across South Korea, Turkey&#8217;s northeast, and Argentina, each confirming that fog regimes are tightly bound to local geography. Recent work has pushed further, exploring machine learning approaches to low-visibility prediction, Bayesian decision networks for airport fog forecasting, and the dramatic forecast improvements that come from including irrigation effects in numerical weather prediction over northern India. The Istanbul analysis contributes a critical empirical foundation for such efforts in the eastern Mediterranean, where complex topography and competing maritime influences make statistical or machine-learning fog prediction especially dependent on high-quality, mechanism-resolved training data.</p>
<p>The broader significance of the work lies in what it says about fog as an urban boundary-layer phenomenon. In a megacity, the surface is a patchwork of heat-retaining concrete, vegetated hills, cool water bodies, and engineered drainage basins, and the atmosphere within the lowest few hundred meters responds to that patchwork in ways that standard synoptic-scale models struggle to resolve. By demonstrating that fog frequency varies fivefold within a single metropolitan area and that simultaneous city-wide fog is a rarity, the Istanbul study makes a compelling case for high-resolution, station-specific fog forecasting grounded in physical typing rather than raw visibility statistics. For the aviation sector, which loses millions of dollars annually to low-visibility delays worldwide, and for the growing community of researchers developing fog decision support systems, the message from Istanbul is clear: to predict fog in a megacity, one must first understand that the megacity is not a single climate but an archipelago of microclimates, each with its own fog story written in temperature, moisture, wind, and terrain.</p>
<p><strong>Subject of Research:</strong> Long-term fog climatology and physical typing across three airports in the megacity of Istanbul</p>
<p><strong>Article Title:</strong> A comparative long-term analysis of fog characteristics in the megacity of Istanbul</p>
<p><strong>Article References:</strong> Yoğun, B., Aktaş, C., Bakır, G., Bozdemi̇r, R., Çeli̇k, Ş., &amp; Özdemi̇r, E. T. (2026). A comparative long-term analysis of fog characteristics in the megacity of Istanbul. <em>Theoretical and Applied Climatology, 157</em>(10), Article 685. <a href="https://doi.org/10.1007/s00704-026-06617-w" rel="noopener noreferrer">https://doi.org/10.1007/s00704-026-06617-w</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1007/s00704-026-06617-w" rel="noopener noreferrer">10.1007/s00704-026-06617-w</a></p>
<p><strong>Keywords:</strong> fog climatology, Istanbul, boundary-layer meteorology, advection fog, radiation fog, urban heat island, aviation meteorology, METAR observations, urban microclimate, low visibility, Türkiye, Theoretical and Applied Climatology</p>
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