Dynamics of Atmospheres and Oceans最新文献

{"title":"Impact of ENSO on the genesis potential index of cyclones over the Bay of Bengal during the post-monsoon season","authors":"P. Suneeta ,&nbsp;TVS Udaya Bhaskar ,&nbsp;S.S.V.S. Ramakrishna","doi":"10.1016/j.dynatmoce.2025.101642","DOIUrl":"10.1016/j.dynatmoce.2025.101642","url":null,"abstract":"<div><div>Tropical Cyclones (TCs) are among the most destructive weather phenomena, causing substantial damage to coastal regions and vulnerable communities along the Bay of Bengal. Predicting their formation remains a significant challenge due to the complex interactions between atmospheric and oceanic processes. This study investigates the influence of the El Niño–Southern Oscillation (ENSO) on the Genesis Potential Index (GPI) and the Total Number of Depressions and Cyclones (TNDC) over the Bay of Bengal (5°–20°N, 80°–100°E) during the post-monsoon season (October–December) from 1995 to 2019. Cyclone activity associated with El Niño, La Niña, and Neutral ENSO phases is examined using four GPI formulations based on key atmospheric and oceanic parameters, including a newly developed index from our previous research. The results reveal pronounced ENSO-dependent variations in vertical wind shear, Upper Ocean Heat Content (UOHC), depth of the 26 °C isotherm (D26), Sea Surface Temperature (SST), Sea Surface Height Anomaly (SSHA), latent heat flux, net longwave radiation, and low-level relative vorticity. During La Niña years, reduced vertical wind shear, enhanced low-level cyclonic vorticity, deeper thermocline, higher UOHC, and increased air–sea heat fluxes create a dynamically and thermodynamically favorable environment for cyclone genesis<strong>,</strong> leading to GPI values nearly twice those observed during El Niño and Neutral phases. These findings demonstrate the critical role of ENSO-driven atmospheric–oceanic coupling in modulating cyclone genesis over the Bay of Bengal and highlight the importance of incorporating ENSO-related variability into regional cyclone forecasting and disaster risk management strategies.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"113 ","pages":"Article 101642"},"PeriodicalIF":2.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Boundary layer interaction of immiscible non-Newtonian nanofluids in distinct shear flows with motile microorganisms","authors":"Z. Abbas,&nbsp;S. Goher,&nbsp;M.Y. Rafiq","doi":"10.1016/j.dynatmoce.2025.101629","DOIUrl":"10.1016/j.dynatmoce.2025.101629","url":null,"abstract":"<div><div>This study presents a comprehensive numerical investigation of two-phase boundary layer shear flows involving immiscible non-Newtonian Carreau and Tangent hyperbolic nanofluids incorporating motile microorganisms. The analysis explores the coupled effects of thermophoresis, Brownian motion, and thermal radiation on velocity, temperature, concentration, and microorganism density profiles across distinct shear regions. Incorporating microorganisms within nanofluids enhances thermal conductivity and stabilizes the flow structure, contributing to improved transport phenomena relevant to biomedical, energy, and environmental systems. The governing nonlinear differential equations are transformed into dimensionless form using similarity transformations and solved via the MATLAB bvp4c collocation method to ensure high numerical accuracy. A grid independence test confirms the convergence and stability of the scheme for all parametric variations. The results demonstrate that the Carreau fluid parameter promotes fluid velocity, while an increase in the viscosity ratio and shear strength ratio reduces it. Brownian motion and thermophoresis parameters suppress temperature near the interface, whereas thermal radiation enhances it. The density of motile microorganisms rises with higher bioconvection and Péclet numbers but decreases with increasing microorganism Schmidt number. Quantitative results for skin friction, Nusselt number, Sherwood number, and microorganism density validate the influence of these parameters in both regions. The findings provide valuable insights for optimizing microfluidic transport, bioconvective systems, and nanofluid-based heat exchangers where multi-phase shear interactions and microorganism activity are significant.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"113 ","pages":"Article 101629"},"PeriodicalIF":2.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of heat and mass transfer in an electromagnetically driven ionized tri-hybrid nanofluids flow over a convectively heated cylinder","authors":"Muhammad Naveed Khan ,&nbsp;Shafiq Ahmad ,&nbsp;Aamir Abbas Khan ,&nbsp;Mounirah Areshi ,&nbsp;Ibrahim E. Elseesy","doi":"10.1016/j.dynatmoce.2025.101635","DOIUrl":"10.1016/j.dynatmoce.2025.101635","url":null,"abstract":"<div><div>Nanofluids are employed in various heat transfer and cooling applications because of their enhanced thermal conductivity, making them useful for electronics cooling, solar collectors, and heat exchangers. The current study explores the behavior of a partially ionized Prandtl fluid with three types of nanoparticles as it flows through a convectively heated cylinder under magnetic influence. The purpose of dispersing three different nanoparticles <span><math><mrow><mfenced><mrow><mi>MWCNT</mi><mo>,</mo><mi>A</mi><msub><mrow><mi>l</mi></mrow><mrow><mn>2</mn></mrow></msub><msub><mrow><mi>O</mi></mrow><mrow><mn>3</mn></mrow></msub><mo>,</mo><mi>SiC</mi></mrow></mfenced></mrow></math></span> is to increase the functional fluid heat transfer rate. The study looks at how powerful produced magnetic and electric fields affect fluid flow under the supposition that the magnetic Reynolds number is very high. The study analyzes the mass and heat equations while taking into account factors like Joule heating, activation energy, varying thermal conductivity, and changing mass diffusivity. Additionally, the consequences of Joule heating, viscous dissipation, and thermal radiation are appraised when evaluating the disorder in the flow system through entropy generation. Based on these assumptions, differential equations were employed to create the mathematical model. The differential equations are then subjected to similarity variables to become a dimensionless variant of ordinary differential equations. The numerical scheme BVP4C on MATLAB has been used to find the numerical results. The comparison results are found for ternary nanofluid <span><math><mrow><mfenced><mrow><mi>MWCNT</mi><mo>,</mo><mi>A</mi><msub><mrow><mi>l</mi></mrow><mrow><mn>2</mn></mrow></msub><msub><mrow><mi>O</mi></mrow><mrow><mn>3</mn></mrow></msub><mo>,</mo><mi>SiC</mi></mrow></mfenced></mrow></math></span> and unary nanofluid <span><math><mrow><mfenced><mrow><mi>A</mi><msub><mrow><mi>l</mi></mrow><mrow><mn>2</mn></mrow></msub><msub><mrow><mi>O</mi></mrow><mrow><mn>3</mn></mrow></msub></mrow></mfenced></mrow></math></span> using graphs. It is observed from the figures that in enhancement in Prandtl first parameter, curvature parameter, Hall and ion slip effect, the fluid motion enhances while the reverse behavior is observed for Hartman number. The fluid temperature surges with stronger estimations of the Dufour number, variable thermal conductivity, and radiation parameter.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"113 ","pages":"Article 101635"},"PeriodicalIF":2.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rainfall extremes variability, teleconnections with atmospheric circulation anomalies in the Indian summer monsoon","authors":"Anmol Yadav ,&nbsp;G.P. Singh ,&nbsp;Pradeep Kumar Rai ,&nbsp;Vijay Kumar Soni ,&nbsp;Akhilesh Mishra ,&nbsp;Sonu Kumar","doi":"10.1016/j.dynatmoce.2025.101636","DOIUrl":"10.1016/j.dynatmoce.2025.101636","url":null,"abstract":"<div><div>We investigate the spatiotemporal variability of Indian Summer Monsoon Rainfall (ISMR) and the anomalies in atmospheric circulation and oceanic conditions during June–September (JJAS) from 1981 to 2022. Using multiple data sources (like IMD, NOAA PSL and HadISST), Empirical orthogonal function (EOF), principal component (PCs) coefficient of variation (CV), precipitation concentration index (PCI), composite analysis of atmospheric and oceanic anomalies determines the variability for exploring extreme wet and dry years. Seasonal rainfall is highest over Northeast India and Western Ghats, while the decadal trend shows increased rainfall in July, August, and September. EOF analysis shows that first mode covers central and southern India, whereas the second mode exhibits a dipole pattern over the Gangetic plains and southern regions with 14.9 % and 9.1 % of the total variance. Eight extremely wet and six extremely dry years were also noted. In composite analysis, wherever extreme wet and dry years are found, these modes correspond to distinct Sea Surface Temperature (SST), Sea Level Pressure (SLP) and wind anomalies across oceanic regions. Wet years exhibit positive rainfall anomalies related with warm SST in Indian Ocean and cooler SST in the Niño 3.4 region, accompanied by low SLP anomalies and enhanced south-westerly wind. Dry years are characterized by cooler SST in the Indian Ocean, warmer Nino 3.4, SST, higher SLP, weak winds, and limited moisture transport, which contribute to the reduction in monsoon activity. These findings underscore the significant role of SST, SLP, wind, and vertical motion, vertically integrated moisture flux and soil moisture anomalies influencing ISMR patterns.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"113 ","pages":"Article 101636"},"PeriodicalIF":2.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning for sea surface temperature prediction in the Indian Ocean: A comparative study using 1D-CNN, LSTM, 1DCNN-LSTM and attention based 1DCNN-LSTM architectures","authors":"B. Sheela Rani ,&nbsp;D. Sathya Narayanan ,&nbsp;M.B. Salma Jasmine ,&nbsp;N.R. Krishnamoorthy ,&nbsp;M. Roja Raman ,&nbsp;Aneesh A. Lotliker ,&nbsp;Abhisek Chatterjee","doi":"10.1016/j.dynatmoce.2025.101632","DOIUrl":"10.1016/j.dynatmoce.2025.101632","url":null,"abstract":"<div><div>Anthropogenic activities had led to major climate changes, causing the oceans to warm rapidly. Subsequently, there is a need for accurate prediction of sea surface temperature (SST). The dynamic Indian Ocean climate, weather and marine ecology is significantly affected by SST changes. In this study, hourly and daily SST data, specifically from 15 and 7 RAMA stations (1 m deep) respectively, at different parts of Indian Ocean is utilized to forecast SST using four deep learning techniques; 1D Convolutional Neural Network (1D-CNN), Long Short-Term Memory (LSTM) network, 1DCNN-LSTM network and attention based 1DCNN-LSTM Architecture. The SST data obtained from RAMA buoy is trained using a sliding window method and model performance is evaluated based on evaluation matrices like Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute error (MAE). The results indicated that 1DCNN-LSTM outperforms 1D-CNN and LSTM at most sites, consistently achieving lower MSE, RMSE and MAE. The findings also revealed that in places where SST shifts significantly, the new attention based 1DCNN-LSTM model often competes with or does better than all the other models in MAE. Distinctive physical phenomena like equatorial jets, thermohaline stratification, monsoon, Indian Ocean Bipolar (IOD) and El Niño-Southern Oscillation (ENSO) bring about geographical difference in performance. Hence, the study illustrates how deep learning frameworks make better SST predictions in complex ocean basins and thereby aids in anticipating climate change.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"113 ","pages":"Article 101632"},"PeriodicalIF":2.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transient mixed convection in coaxial pipes with temperature-dependent variable density","authors":"Bakhtawar Bibi ,&nbsp;Ali B.M. Ali ,&nbsp;Muhammad Ashraf ,&nbsp;Ghulam Rasool ,&nbsp;Muhammad Usman Rashid ,&nbsp;Abduvali Sottarov","doi":"10.1016/j.dynatmoce.2026.101649","DOIUrl":"10.1016/j.dynatmoce.2026.101649","url":null,"abstract":"<div><div>This study investigates the effects of temperature-dependent variable density on mixed convective heat transfer in coaxial pipes. The inner pipe’s surface is stationary and uniformly heated, with flow along its axis, while the outer wall is placed at infinity. A two-dimensional time-dependent flow and temperature field are modeled using coupled nonlinear partial differential equations, solved numerically via the implicit finite difference method. Simulations explore a range of parameters to predict thermal efficiency, steady-state velocity, temperature distribution, dynamic surface shear, and energy shear. Results show that increasing the density variation parameter (m = 0.1, 1.5, 2.0, 2.5) enhances fluid velocity and thermal distribution, peaking at m = 2.5. Energy shear increases with mm, reaching a maximum at m = 0.7, while surface shear remains uniform. These findings provide insights into optimizing thermal performance in coaxial flow systems.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"113 ","pages":"Article 101649"},"PeriodicalIF":2.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147394353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Surface wave-induced modulation of submesoscale fronts: A process governed by model resolution","authors":"Cheng Peng ,&nbsp;Peng Wang ,&nbsp;Dongxiao Wang","doi":"10.1016/j.dynatmoce.2026.101645","DOIUrl":"10.1016/j.dynatmoce.2026.101645","url":null,"abstract":"<div><div>Submesoscale fronts in marginal seas typically exhibit complex generation mechanisms that are highly dependent on local background flows and various forcing factors, such as winds, tides, etc. Among these forcing factors, the influence of waves remains under-research. This study investigates the effects of surface gravity waves on submesoscale fronts in the Northern South China Sea using numerical simulations. Simulation results indicate that the intensity of submesoscale fronts is significantly affected by waves. However, unlike previous studies in which the wave-induced Stokes vortex force is found to enhance frontal structures, in the present study, the Stokes vortex force is weak and negligible at kilometer-scale model resolution. Instead, the Stokes Coriolis force, another wave-induced force, contributes to the momentum balance, resulting in the transition of turbulent thermal wind (TTW) to Stokes-TTW at the submesoscale fronts. Furthermore, the Stokes Coriolis force triggers an anti-Stokes flow, which opposes the Eulerian current in the study area. As a result, the current is weakened, reducing the current-induced frontogenesis and ultimately diminishing the intensity of submesoscale fronts.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"113 ","pages":"Article 101645"},"PeriodicalIF":2.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensitivity analysis of the physics options in the Weather Research and Forecasting model and its impact on storm surge simulations during two tropical cyclones over the Bay of Bengal","authors":"Vyshnavi Sai Yalla ,&nbsp;A.N.V. Satyanarayana ,&nbsp;P.L.N. Murty ,&nbsp;K.Siva Srinivas","doi":"10.1016/j.dynatmoce.2025.101643","DOIUrl":"10.1016/j.dynatmoce.2025.101643","url":null,"abstract":"<div><div>Accurate prediction of tropical cyclones and associated storm surges over the Bay of Bengal (BoB) is crucial for disaster risk reduction and coastal planning. In the present study, a high-resolution mesoscale model, WRF-ARW 4.0 is used and conducted sensitivity experiments with eight combinations of four cloud microphysics schemes (Lin, WSM6, Thompson, WDM6) and two planetary boundary layer schemes (YSU and MYJ) to evaluated the best combination in simulating the outer and inner core wind intensity and cyclone track of two severe cyclones, Amphan and Yaas over BoB. The simulations of wind and cyclone tracks are validated along the best track of the India Meteorological Department. The analysis of the results reveals that the combination of physical schemes, Thompson with YSU, and WSM6 with YSU, reasonably captures the inner and outer core winds and track of cyclones with a mean error of 4.2–8.5 ms⁻¹ and 48–105 km, respectively. The simulations of the eight combinations of physics schemes are utilised in a coupled hydrodynamic model of ADCIRC and SWAN to assess storm surges and significant wave heights. The simulated storm surges are validated using available tide gauge observations at Paradip (20.2817° N, 86.6727° E) and Dhamra (20.8237° N, 86.9640° E) port for the Amphan and Yaas cyclone, and simulations of significant wave heights are validated against moored buoy observations at BD08 (18.1613° N, 89.6702° E) and BD09 (17.8563° N, 89.6772° E) locations. Statistical analysis using Taylor diagrams revealed that the WRF model with the two physics combinations, Thompson–YSU and WSM6–YSU, demonstrated improved accuracy in predicting storm surges and significant wave heights during both cyclones. The findings identify the performance of an appropriate physics combination of the WRF model for improved storm surge predictions over the BoB cyclones.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"113 ","pages":"Article 101643"},"PeriodicalIF":2.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coastal water level trends and ENSO-related variability in the northeastern Mekong Delta (1979–2024)","authors":"Vu Duy Vinh ,&nbsp;Sylvain Ouillon ,&nbsp;Nguyen Minh Hai","doi":"10.1016/j.dynatmoce.2026.101648","DOIUrl":"10.1016/j.dynatmoce.2026.101648","url":null,"abstract":"<div><div>Coastal water levels in the northeastern Mekong Delta exhibit pronounced long-term trends and interannual variability linked to large-scale climate forcing. Using tide-gauge observations at the Vam Kenh station (1979–2024) and CMEMS (Copernicus Marine Environment Monitoring Service) satellite altimetry (1993–2024), we assess long-term, seasonal, and ENSO-related water level variability. The results reveal a statistically significant and evidence of recent acceleration inferred from sub-period trends in mean relative water level, with rates exceeding approximately 6 mm yr⁻¹ over the last two decades (2005–2024), compared to about 5 mm yr⁻¹ over the full 46-year record. Seasonal variability shows modulation of the rise by the monsoon cycle, with faster increases during the northeast monsoon and slower rises during the southwest monsoon. Interannual variability is clearly modulated by the El Niño–Southern Oscillation, with strong La Niña events elevating water levels by up to about 5 cm in anomaly magnitude, while El Niño phases are generally associated with negative anomalies. Atmospheric pressure acts as a secondary control, contributing approximately 5–20 % of interannual variance through the inverse barometer effect. Tide-gauge and CMEMS data exhibit strong agreement (r = 0.95), supporting their combined use for coastal monitoring. Overall, the results highlight accelerating relative rise in a subsiding deltaic environment, with important implications for coastal vulnerability.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"113 ","pages":"Article 101648"},"PeriodicalIF":2.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147394352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk mapping of dynamic dust storms and multi-hazard maritime navigation in the red sea using machine learning and MODIS Data","authors":"Yazeed Alsubhi ,&nbsp;Bassam M. Aljahdali ,&nbsp;Ayman F. Alghanmi ,&nbsp;Hussain T. Sulaimani ,&nbsp;Ahmad E. Samman","doi":"10.1016/j.dynatmoce.2025.101621","DOIUrl":"10.1016/j.dynatmoce.2025.101621","url":null,"abstract":"<div><div>Dust storms represent a significant hazard to maritime navigation, particularly in regions such as Saudi Arabia, where frequent dust events, driven by vast desert landscapes and oceanic wind patterns, reduce visibility and disrupt maritime operations. This paper proposes a comprehensive framework for evaluating visibility risks posed by dust storms in Saudi Arabian maritime zones, specifically focusing on the Red Sea. The methodology considers MODIS AOD (Aerosol Optical Depth) data, wind speed, and cloud cover to develop a dynamic risk assessment model using random forest (RF) for dust storm detection and visibility risk prediction. The model integrates spatial data layers for environmental factors (wind, waves, and depth), creating seasonal risk maps that dynamically adjust based on changing environmental conditions. GIS technology was used to visualize risk zones, and the RF model provided data-driven weighting of risk factors. The model’s performance was validated using metrics such as probability of detection (POD) (0.92), probability of false detection (PFD) (0.05), and equitable threat score (ETS) (0.85), demonstrating superior accuracy over traditional methods like analytic hierarchy process (AHP) and CRiteria importance through intercriteria correlation (CRITIC). The findings indicate that Autumn represents the most hazardous season for maritime navigation due to frequent dust storms, with the central Red Sea being the most impacted area. The results demonstrate the potential of this approach for improving navigation safety and early warning tools in the Red Sea and similar arid coastal regions.</div></div>","PeriodicalId":50563,"journal":{"name":"Dynamics of Atmospheres and Oceans","volume":"113 ","pages":"Article 101621"},"PeriodicalIF":2.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}