ABSTRACT Extreme convective events are posing increasing challenge to aviation. On December 13, 2024, an intense thunderstorm caused severe operational disruption at Rome–Fiumicino Airport. Here we analyze the dynamic and thermodynamic conditions associated with this event using a conditional analogue‐based framework applied to ERA5 reanalysis data. We identify synoptic and mesoscale patterns similar to the one observed during the event over the satellite era (1979 to present) and compare the associated environmental conditions between a counterfactual past period (1979–2000) and a factual present one (2002–2023). While the dynamical structure of the circulation patterns remains mostly unchanged, the thermodynamic background has evolved toward warmer conditions, with increased near‐surface air and sea surface temperatures over the Mediterranean basin. These changes are accompanied by increases in precipitation, convective instability, and wind shear. Observations at Rome–Fiumicino Airport further indicate stronger wind gusts, increased dew‐point temperature and reduced visibility during analogue situations in recent decades. Our results suggest that warming background conditions may amplify the convective impacts of otherwise similar synoptic and mesoscale patterns, increasing the potential for disruptive weather affecting Mediterranean aviation hubs.
ABSTRACT The rapid and unprecedented warming of the Indian Ocean intensifies climate risks across socio‐economically vulnerable regions, highlighting the need of accurate prediction over the coming decade. This study first assesses the decadal predictability of the Indian Ocean Dipole (IOD) using the Decadal Climate Prediction Project (DCPP) models of Coupled Model Intercomparison Project Phase 6 (CMIP6), then develops a deep learning model based on a bidirectional gated recurrent unit (BiGRU) to enhance its predictive skill. The BiGRU model is designed to process multisource sequential data and is trained on the IOD index derived from DCPP simulations. Results show the MME achieves moderate skill on detrended IOD with an anomaly correlation coefficient (ACC) and mean squared skill score (MSSS) of 0.51 and 0.20 during 1963–2020, respectively. The BiGRU model improved the skill with an anomaly correlation coefficient (ACC) of 0.88 and a mean squared skill score (MSSS) of 0.72 during the testing period of 2009–2020, and accurately captured extreme IOD events. Based on the enhanced IOD index, we further used it to improve the prediction skill of the IOD‐related Australian rainfall, achieving ACC and MSSS values of 0.90 and 0.70 during 2009–2020, compared to 0.29 and −1.62 from the MME, underscoring the reliability of the BiGRU model for both IOD and related precipitation forecasts.
ABSTRACT Satellite detections of hail signatures are uncertain in the tropics, where the deep troposphere and a warm, humid sub‐cloud environment increase the chances that ice detected aloft will melt before it reaches the surface. It is often suspected that satellite‐based detections of hail over the tropics are over‐estimations owing to this effect. Here, we used numerical weather simulations to examine the plausibility of damaging surface hail at times and locations when satellites detected hail signatures over Australia's tropics. Four microphysics schemes were used to simulate 61 hail signature detections with surface hailstone sizes estimated using a column model for hailstone growth and melting, and estimated by model microphysics. Using the column model, 65 of the 244 simulations were “damaging‐hail cases” that produced surface hail at least 20 mm in diameter. Although instability was not significantly different between the no‐hail and damaging‐hail cases, damaging‐hail cases had increased wind shear and mid‐ to upper‐level moisture, and produced storms with wider and stronger updrafts than no‐hail cases. These hail cases could therefore support the growth of larger hailstones that survived melting to reach the surface. The results are well explained by entrainment theory. These simulations show that satellite‐based hail detections in the tropics may plausibly contain a significant subset of damaging surface‐hail events.
ABSTRACT Lake‐breeze fronts (LBFs) are important drivers of cloudiness, deep moist convection, and heavy precipitation around large tropical lakes, yet their representation in global forecast systems remains poorly understood. This study evaluates the ability of the ECMWF Integrated Forecasting System (IFS) 9 km operational analyses to represent the lake‐breeze system over the Lake Victoria basin in Uganda during December–February and June–August 2017–2022. A recently developed objective lake‐breeze detection algorithm (OLBDA) is applied to hourly station data and IFS surface data to identify LBF passages. Results show that while the IFS captures the coherent progression of the LBF from early to late afternoon, the analysis reveals biases, including an overprediction of LBF occurrence by ~26% and an early arrival of 1–2 h at most stations. Among three commonly used parameters to delineate LBFs, that is, surface convergence, and gradients of surface specific humidity and boundary‐layer height (BLH), the latter two emerge as the most reliable indicators of LBF structure and evolution. Composite and vertical cross‐section analyses reveal physically consistent three‐dimensional lake‐breeze features in the IFS, yet contrasts occur between western and northern transects. The NW‐SE transect shows stronger vertical motion and deeper inland penetration when compared to the North–South transect. The latter is likely related to the mean easterly low‐level flow over the lake. The depth of the BLH in the late afternoon is 3 km. Overall, our results suggest that ECMWF IFS operational analyses can be reliably used to study lake‐breeze systems in both observational and modeling contexts.
ABSTRACT The South Indian Ocean High‐Pressure (SIOHP) system strongly influences regional climate and oceanic circulation, yet a comprehensive index of its variability is lacking. We extend an earlier methodology for subtropical highs to develop an index of SIOHP intensity and position and describe its spatial and temporal variability from 1940 to 2023 using ERA5 mean sea level pressure. The SIOHP shows clear inter‐ and intra‐annual variability, with the highest intensities in winter (JJA) and spring (SON) and a pronounced seasonal migration. In the transition seasons, and most clearly in November, the centroid is bimodally distributed: a composite of the raw pressure field resolves two distinct closed anticyclones, a strong, compact southeastern high and a weaker, northwestward‐displaced high about 4 hPa weaker, showing that the SIOHP alternates between two physical configurations differing in both position and strength rather than a single migrating feature. We assess the influence of the El Niño Southern Oscillation (ENSO) using a trend‐corrected, ENSO‐year classification based on the Relative Oceanic Niño Index. Contrary to earlier expectations, ENSO exerts only a weak and largely insignificant influence: neither seasonal position nor intensity is significantly modulated by ENSO phase, and no significant distinction emerges between canonical and Modoki events. The one robust signal is an equatorward displacement of the high during El Niño summer (DJF). Interannual SIOHP variability therefore appears to be governed largely by factors other than ENSO, which may include internal atmospheric variability, regional air‐sea coupling, and remote influences from outside the tropical Pacific. The index offers a tool for monitoring, forecasting, and assessing regional climate variability.
ABSTRACT Tropical cyclones (TCs) and the East Asian trough (EAT) are prominent circulation systems over the Western North Pacific (WNP)–East Asia region. Using statistical analysis, this study investigates the remote influences of TC activity over the tropical WNP on the location of the EAT and examines the possible underlying reasons. Results show that TC activity can cause the EAT line to move northwestward. The anomalous geopotential height induced by the remote influence of TC activity is a key factor in displacing the EAT, with the EAT line shifting away from regions with positive anomalous geopotential height. The anomalous warm advection and anomalous latent heat release induced by TC activity over the region east of the EAT line result in positive temperature anomalies, which further generate positive geopotential height anomalies under the constraint of static equilibrium, ultimately displacing the EAT. Findings of this study reveal the important modulating role of WNP TC activity on the East Asian mid‐latitude climate system.
ABSTRACT Four equilibrium climate simulations using the Community Earth System Model version 2.2 forced by prescribed Sea Surface Temperature (SST). The model mesh was regionally refined to 0.25° horizontally over the Asia‐Pacific, in order to generate intense typhoons (maximum sustained winds above 41.5 m s−1). Two baseline simulations were forced by SSTs of 1997 (El Niño), 2000 (La Niña). The global SST was detrended by removing Mode 1 from Empirical Orthogonal Function decomposition. Two more “non‐warming” simulations of 1997 and 2000 were performed. Intense typhoon tracks were grouped with agglomerative hierarchical clustering and categorized into westward and curved tracks. Mode 1 decreased the number of westward tracks for 2000, while there were no statistically significant changes in curved tracks for 2000 and both types for 1997. Mode 1 also increased track density over the Luzon Strait toward Guangdong in 1997 (not significant), and over the Yangtze River mouth in 2000 (significant). It is therefore possible that the perceived increased typhoon damage in recent years may be due to intense typhoon tracks shifting to more populated and economically important regions. However, since only 2 years were analyzed, the track changes may be due to residual SST anomalies that were event‐specific. Furthermore, there remained uncertainty in the individual effects of global warming and climate variability signals contained inside Mode 1.
ABSTRACT In this study, probabilities of tropical cyclogenesis in the Bay of Bengal (BoB) were analyzed across the full two‐dimensional phase space of the real‐time multivariate Madden–Julian oscillation (MJO) (RMM) index for pre‐ and post‐monsoon periods from 1990 to 2025. Results show that cyclogenesis anomalies span the phase space and depend largely on the sign of the first principal component of the index, RMM1. Moreover, on days when the intraseasonal index is in phases previously found favorable for cyclogenesis, the anomalies are statistically significant for only a limited range of amplitudes in those phases. Skill scores were calculated for vertical velocity (VV), relative humidity (RH), sea level pressure (SLP), vertical wind shear (VWS), and sea surface temperature (SST) to quantify how well each parameter identifies cyclogenesis in the intraseasonal phase space. Among these variables, 700‐hPa VV was most skillful at identifying both pre‐ and post‐monsoon cyclogenesis anomalies, outperforming RH, SLP, VWS, and SST, although all had high false alarm ratios. The 700‐hPa VV was also more skillful than the 500‐hPa VV, suggesting that it should be included in intraseasonal genesis indices. In the post‐monsoon period, SST showed little to no skill at identifying intraseasonal cyclogenesis anomalies, in agreement with recent work suggesting it be considered alongside other modes of variability. The results of this study fill a critical gap in our understanding of the MJO–tropical cyclone relationship in the BoB by establishing basin‐specific probabilities of cyclogenesis across multiple MJO states and identifying drivers of the variability.
Continuous monitoring of boundary layer turbulence remains a challenge due to sparse conventional instrumentation. Here we suggest that spectral analysis of Global Navigation Satellite System (GNSS) zenith wet delay (ZWD) fluctuations yields physically meaningful diagnostics of boundary layer state. From 3 years of co-located GNSS and Doppler lidar observations (January 2022-December 2024, ) at Payerne, Switzerland, we extract the variance , a measure of integrated water vapor turbulence intensity, and the cutoff frequency , which marks the spectral extent of turbulent mixing. Annual harmonic analysis reveals that captures 54% of its variance through the seasonal cycle (, peak in January), while peaks in August (). The inverse - coupling () tightens to under summer convective conditions, consistent with regime-dependent physical correspondence. Cross-instrument comparison with Doppler lidar turbulent kinetic energy (TKE) integrated over 100-550 m is compatible with the fundamental vertical sampling mismatch between troposphere-weighted GNSS and profile-limited lidar measurements. These results establish GNSS networks as a globally available sensing system for boundary layer turbulence monitoring.
ABSTRACT Recent increases in summer extreme rainfall over North China pose growing societal risks, yet their long‐term evolution and governing mechanisms remain poorly understood. Systematic analysis of observations from 1979 to 2021 reveals a discernible interdecadal change in extreme rainfall around the early 2000s, transitioning to a wetter period characterized by increased mean values and accelerated trends. Unlike the late‐1970s interdecadal change of rainfall, this recent increase of extreme rainfall occurred alongside a weakened East Asia summer monsoon, implying distinct drivers. Acting alongside global warming, two key internal variability mechanisms amplify the rise in extreme rainfall: (1) phase reversals of the Pacific Decadal Oscillation (negative) and Atlantic Multidecadal Oscillation (positive) established an upper‐level divergent and lower‐level convergent anomaly, sustaining ascent over North China via a poleward‐shifted East Asian westerly jet and adjusted associated secondary circulation; and (2) Indian Ocean warming drove the western Pacific subtropical high to strengthen, extend westward, and shift northward, intensifying southeasterly moisture transport. Together, these oceanic forcings set favorable dynamic and thermodynamic conditions for increased extremes.
ABSTRACT Understanding the impact of marine meteorological observations is crucial for improving atmospheric analyzes, particularly in data‐sparse oceanic regions. This study investigated the impact of marine meteorological observations on atmospheric forecasts over the eastern tropical Indian Ocean, using the Ensemble‐based Forecast Sensitivity to Observations (EFSO) technique. 17‐year statistics revealed pronounced seasonality; impacts were significantly greater during boreal winter than in summer, despite comparable observation frequencies. Focusing on moored buoys, the results showed a strong correspondence between observation impacts and the intensity of atmospheric disturbances. High impacts were spatially aligned with eastward‐propagating moist convective disturbances such as the Madden–Julian Oscillation (MJO). The impact of the buoys near 95°E increased across a broad area associated with MJO passage. Even behind the MJO‐active phase, enhanced impacts were detected from small‐scale moist convective disturbances, though their spatial influence was more limited. Observation type comparison revealed that near 95°E, the impact of surface marine observations increased markedly with convective activity, accompanied by enhanced satellite‐derived impacts. Moist energy accounted for the largest share of the total observation impacts, followed by kinetic energy, highlighting the role of near‐surface marine observations in improving the representation of low‐level moisture and wind structures essential for the development of moist atmospheric disturbances.
ABSTRACT In early winter of 2023 (December 9th–23rd), a record‐breaking cold event hits northeastern China (NEC), resulting in serious economic losses and significant disruptions to daily life. Our analysis suggests that this cold event is attributed to the preceding extreme negative phase of the North Atlantic Oscillation (NAO). The NAO‐related Barents–Kara Seas high (BKH) leads to the southward invasion of polar cold air into Siberia. The accumulation of cold air favors the enhancement of the Siberian high. In addition, at the upper level, the BKH induces upper‐level convergence and downward motion over Siberia. The accumulated cold air and downward motion jointly favor the development and maintenance of the historically strongest Siberian high in December 2023. Accordingly, the strong northerly winds associated with the strongest Siberian high transport cold air southward to NEC, resulting in the record‐breaking cold event over the region in December 2023.
ABSTRACT Probabilistic atmospheric forecasts are useful for disaster management and a variety of socioeconomic activities. One avenue to improve these forecasts is through advancing our understanding of forecast distributions. This study advances that understanding through a multiscale investigation of 1000‐member free‐running ensembles of a coarse resolution intermediate complexity general circulation model (GCM). We found direct non‐parametric evidence that a time‐varying equilibrium forecast distribution manifests at long lead times (> 40% longer than the variance saturation time). Interestingly, the forecast distribution exhibits the strongest non‐Gaussian characteristics prior to equilibration. That spike in non‐Gaussianity is likely because the forecast distribution encountered the boundary separating physically realistic and unrealistic atmospheric states. The characteristics of the time‐varying equilibrium distribution are also explored. Our findings thus imply that (1) useful information may be present in probabilistic forecasts beyond the variance saturation time, and (2) models of forecast distributions should account for the complicated structures that arise in multivariate forecast statistics prior to equilibration. These implications and our findings merit further investigation using more realistic GCMs.
ABSTRACT Recent observational and modeling studies highlight the growing global impacts of heavy precipitation. Although daily extremes have been widely studied, short‐duration precipitation events that often result in pluvial floods have received less attention. This study analyzes historical changes in hourly precipitation across Japan using observational data and large ensemble simulations with a 20‐km resolution. The findings indicate that human activities have increased the likelihood of hourly precipitation exceeding 30 mm/h. Since the 1980s, the influence of anthropogenic factors has grown more pronounced on hourly extremes than on daily events, suggesting that short‐term precipitation is more sensitive to global warming. In addition, the area prone to heavy precipitation has expanded northward with each passing decade. These results imply that cumulative anthropogenic influences and associated temperature rise have increasingly altered thermodynamic atmospheric environments conducive to convective precipitation. These results highlight the importance of strengthening disaster preparedness in regions that were previously unexposed to short‐term heavy precipitation. Because simulated precipitation relies on a cumulus parameterization scheme, further quantitative assessment using cloud‐resolving models is warranted.
ABSTRACT Forecasting tropical cyclone (TC) activities has long been a major focus. East China (EC) is a key region that is vulnerable to TC originating from the western North Pacific. In this study, we utilize two reanalysis datasets spanning from 1979 to 2009 and propose an effective statistical seasonal forecasting model, named the Sun Yat‐sen University (SYSU) model, to predict the annual TC landfalls on EC based on preseason environmental predictors. Comprehensive predictor sampling and multiple linear regression analysis reveal that the 850‐hPa geopotential height over West Asia and South Pacific in February, the 500‐hPa geopotential height over West Asia in March, and the 300‐hPa geopotential height over North America in April are the key predictors. The correlation coefficient over 1979–2009 between the model results and observations reaches 0.84. The model has been validated by the leave‐one‐out and threefold cross‐validation methods, as well as the recent 15‐year observations (2010–2024). The Pacific Decadal Oscillation, Pacific‐North American pattern, and Arctic Oscillation are proposed to be the possible physical linkages or mechanisms underlying the model. The SYSU model exhibits a 98% hit rate over 1979–2024 (45 out of 46), highlighting the potential for operation.
ABSTRACT Atmospheric Rivers (ARs) are one of the key elements in explaining the occurrence of extreme precipitation and floods in mid‐latitudes. Despite the recognised importance of ARs, few studies have systematically evaluated how a weather forecast model captures AR conditions affecting western Europe. Using radiosonde observations from different sites across western Europe, this study evaluates the specific humidity, wind speed and moisture flux in the data assimilation system of the ECMWF Integrated Forecasting System (IFS) for the extended winter of 2020/2021 with a particular focus on landfalling ARs. Results indicate a systematic underestimation of specific humidity, wind and moisture flux in the IFS, particularly during more intense moisture flux events. The most significant negative biases of the IFS were observed in the boundary layer (1000–900 hPa) and lower free troposphere (900–700 hPa), coinciding with the core region of moisture flux. Wind speed was generally underestimated, with the largest errors occurring in the boundary layer at locations with complex topography. In addition, as expected, the assimilation of radiosonde profiles reduced short‐range forecast errors. The results highlight the current limitations in forecasting AR intensity and location and show the importance of in situ observations to improve the forecast of high‐impact weather events.
ABSTRACT This study investigates the climatological characteristics of remote rainfall in northeastern Taiwan during the cold half‐year of 1980–2023. We identify critical factors driving heavy precipitation when tropical cyclones (TCs) are located south of Taiwan. Spatial analysis reveals distinct rainfall ‘hotspots’ that shift southward from Yilan depending on the TC's specific position. Statistical results indicate that heavy rainfall is primarily governed by extrinsic environmental thresholds, specifically moisture convergence and specific humidity. Validation using 2024–2025 cases confirm the robustness of these thresholds. We conclude that the interaction between background northeasterly flow and TC positioning acts as the dominant control. This relationship suggests that future climate‐induced changes in TC tracks may displace established rainfall hotspots, potentially altering regional hydroclimatic risks.
ABSTRACT Understanding the extent to which human activities have influenced regional climate is a key scientific and policy challenge. The UK is one of the world's best observed regions climatically, with a long and reliable temperature record that makes it an important test case for regional detection and attribution. Here, for the first time, we apply optimal fingerprinting to UK mean 2‐m air temperature changes using the Estimating Equations method, HadUK‐Grid observations, and CMIP6 simulations. We assess the extent to which observed UK temperature changes can be explained by natural internal variability, anthropogenic forcings, and natural external forcings. We detect a significant anthropogenic influence on warming in recent decades and identify greenhouse gases as the main driver. We also detect a cooling contribution from other anthropogenic influences in the mid‐twentieth century, likely dominated by sulphate aerosols. These results update earlier UK‐focused work and demonstrate that human influences, both warming and cooling, are detectable even at the national scale.
ABSTRACT In winter, cold‐air damming (CAD) in Japan's Kanto Plain often results in snowfall, which can seriously affect infrastructure. This study investigated the three‐dimensional structure of CAD during a typical snowfall event on 4 March 2025 based on independently conducted simultaneous multiple‐site radiosonde observations, together with radiosonde observations from the Japan Meteorological Agency and surface observations. The observations revealed a distinct three‐layer structure: the inland cold air with a depth of 500–1000 m over the plain, an overrunning northeasterly to easterly flow, and warm air intruding from the south to southeast. This structure is consistent with the typical CAD observed east of the Appalachian Mountains of the eastern United States, which is characterised by warm air overrunning a cold‐air dome. An examination of the formation process further suggests that this CAD likely formed within a shallow low‐level layer owing to diabatic cooling associated with precipitation. This paper presents an observation‐based case study that documents the three‐dimensional structure of CAD, as well as an aspect of its temporal evolution over the relatively understudied Kanto Plain.
ABSTRACT Probable maximum precipitation (PMP) is crucial for water‐related disaster management, especially in regions like Nepal, where extreme weather poses significant risks. Despite its importance, PMP studies in Nepal remain limited. This study quantifies PMP using Hershfield's method, applied to daily precipitation data at 0.05° resolution from CHIRPS v2.0 (1992–2022), compared against in situ observations (correlation coefficient = 0.80, index of agreement = 0.68, RMSE = 4.56 mm). Intense rainfall (> 70 mm/day) is prevalent in central, eastern, and lower western Nepal from June to September, with an increasing trend in pre‐monsoon (March–May) rainfall, suggesting a potential shift toward an earlier monsoon onset. In contrast, post‐monsoon (October–November) rainfall is declining, particularly in western Nepal. The trend in extreme precipitation (total precipitation on heaviest 1% of days) shows a statistically significant increase of 16 mm/year (p < 0.05) across the eastern and Churia range. In contrast, the western and northern regions experienced a significant decline of approximately 14 mm/year (p < 0.05). PMP values peak at around 920 mm/day in certain grids over western Nepal and 540 mm/day in the central Himalayas and mid‐hills, highlighting serious hydrological risks such as floods, landslides, and dry spells. The findings underscore the urgency of improved early warning systems, resilient infrastructure, and adaptive climate policies.
