Atmospheric Science Letters最新文献

{"title":"VARiational Analysis of Nonhydrostatic Dynamics Using Short-Time Delayed Microwave Measurements, VARAND2","authors":"Thomas Lefebvre, Hélène Brogniez, Laura Hermozo, Frédéric Chevallier","doi":"10.1002/asl2.70063","DOIUrl":"https://doi.org/10.1002/asl2.70063","url":null,"abstract":"<p>Deep convective clouds play a central role in the Earth water and energy cycles, yet their rapid vertical development remains difficult to characterize. The C<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mrow></mrow>\u0000 <mn>2</mn>\u0000 </msup>\u0000 </mrow>\u0000 <annotation>$$ {}^2 $$</annotation>\u0000 </semantics></math>OMODO mission relies on a tandem of two passive microwave radiometers flying sequentially with a time separation ranging from 45 to 135 s. This configuration enables the estimation of short-time brightness temperature differences that informs on convective dynamics. In this study, we introduce VARAND<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mrow></mrow>\u0000 <mn>2</mn>\u0000 </msup>\u0000 </mrow>\u0000 <annotation>$$ {}^2 $$</annotation>\u0000 </semantics></math>, a one-dimensional variational method that exploits multi-temporal passive microwave observations like those provided by C<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mrow></mrow>\u0000 <mn>2</mn>\u0000 </msup>\u0000 </mrow>\u0000 <annotation>$$ {}^2 $$</annotation>\u0000 </semantics></math>OMODO to retrieve key dynamical properties of deep convection. VARAND<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mrow></mrow>\u0000 <mn>2</mn>\u0000 </msup>\u0000 </mrow>\u0000 <annotation>$$ {}^2 $$</annotation>\u0000 </semantics></math> retrieves the vertical profile and short-time evolution of the Ice Water Content (IWC), as well as a parametrized vertical profile of air vertical velocity (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>w</mi>\u0000 <mi>air</mi>\u0000 </msub>\u0000 </mrow>\u0000 <annotation>$$ {w}_{mathrm{air}} $$</annotation>\u0000 </semantics></math>), characterized by its maximum amplitude (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>w</mi>\u0000 <mi>max</mi>\u0000 </msub>\u0000 </mrow>\u0000 <annotation>$$ {w}_{mathrm{max}} $$</annotation>\u0000 </semantics></math>) and the corresponding altitude (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>z</mi>\u0000 <mi>max</mi>\u0000 ","PeriodicalId":50734,"journal":{"name":"Atmospheric Science Letters","volume":"27 10","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl2.70063","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149205923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bridging Artificial Intelligence and Data Assimilation: The Data-Driven Ensemble Weather Forecasting System ClimaX-LETKF","authors":"Akira Takeshima,&nbsp;Kenta Shiraishi,&nbsp;Atsushi Okazaki,&nbsp;Tadashi Tsuyuki,&nbsp;Shunji Kotsuki","doi":"10.1002/asl2.70062","DOIUrl":"https://doi.org/10.1002/asl2.70062","url":null,"abstract":"<p>While machine learning-based weather prediction (MLWP) has achieved significant advancements, research on assimilating real observations or ensemble forecasts within MLWP models remains limited. We introduce ClimaX-LETKF, the data-driven ML-based ensemble weather forecasting system that combines the MLWP model ClimaX with a conventional data assimilation program. It operates stably over multiple years, independently of numerical weather prediction (NWP) models, by assimilating the NCEP ADP Global Upper Air and Surface Weather Observations. The system demonstrates similar analysis errors with both relaxation to prior perturbation (RTPP) and relaxation to prior spread (RTPS) when optimal relaxation parameters were applied. RTPP replaces an analysis perturbation with a weighted blend of analysis and background perturbations, whereas RTPS simply rescales the analysis perturbation. A substantial reduction in the ensemble spread was observed at the first forecast timestep when initialized from analyses produced with RTPS, indicating weaker initial ensemble spread growth than with RTPP. This work demonstrates stable long-term data assimilation cycling with a MLWP model using real observations and represents an important step toward practical, self-sustained MLWP forecasting systems.</p>","PeriodicalId":50734,"journal":{"name":"Atmospheric Science Letters","volume":"27 10","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl2.70062","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149205922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Observational Characteristics and Meteorological Drivers of Inferior Mirages in Kumtag Desert, China","authors":"Liangluan Song,&nbsp;Wenjie Zhou,&nbsp;Shuihua Song,&nbsp;Ronggang Bao,&nbsp;Huiqin Zhang","doi":"10.1002/asl2.70064","DOIUrl":"https://doi.org/10.1002/asl2.70064","url":null,"abstract":"<p>Mirages are virtual images formed when light reflected from surface objects is refracted by the atmosphere, and they are generally classified into superior and inferior mirages. The Kumtag Desert in Xinjiang, China, strong near-surface vertical temperature lapse rates are common there, favoring the occurrence of inferior mirages. The annual occurrence frequency reaches 98.9%. Using in real-time camera monitoring mirage images and meteorological data collected from September 2022 to August 2024, this study analyzed the observational characteristics and meteorological drivers of inferior mirages. Based on the occurrence period, image coverage, boundary clarity, and morphological characteristics, inferior mirages can be divided into three grades. The results show that the duration of inferior mirages in the Kumtag Desert is longer in summer and shorter in winter, and the mirage intensity level is higher in summer and lower in winter. Mirages are most frequently observed from 10 to 18 and are clearest around noon. The morphological features of mirages decrease with increasing observation height. Mirage level is positively correlated with air temperature, visibility, sunshine duration, near-surface temperature (0–100 cm), vertical temperature difference, and wind speed, and negatively correlated with relative humidity. Therefore, mirages are more likely to occur on sunny days in the warm season.</p>","PeriodicalId":50734,"journal":{"name":"Atmospheric Science Letters","volume":"27 10","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl2.70064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149205349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climate Change Contribution to Seasonal Forecast Anomalies Using Constrained CMIP6 Projections","authors":"Louis Ledoux--Xatard,&nbsp;Damien Specq,&nbsp;Saïd Qasmi,&nbsp;Hervé Giordani","doi":"10.1002/asl2.70061","DOIUrl":"https://doi.org/10.1002/asl2.70061","url":null,"abstract":"<p>The climate anomalies predicted by real-time seasonal forecasts are constructed with respect to a hindcast climatology over a past period. With climate change, the climatology no longer reflects current climate conditions, systematically biasing predictions toward warm anomalies and complicating their operational use. Therefore, there is a need to properly quantify the signal in seasonal forecasts that arises from long-term climate change. This study introduces a new method to estimate this climate change contribution, as an alternative to the commonly used linear trend on the hindcast period. This method is based on a Bayesian technique called Kriging for Climate Change (KCC) and combines CMIP6 simulations and initialized seasonal hindcasts to estimate the forced response within the model. We apply this method to 2 m-temperature real-time seasonal forecasts from Météo-France and compare it to the linear trend benchmark, with a focus on the June–July–August (JJA) and December–January–February (DJF) seasons, initialized on 1 May and 1 November respectively. Results show that both methods provide similar global patterns but differ in the intensity of the estimated climate change contribution, especially over mid-latitudes. We find that the KCC method is more robust than the linear trend because it is not wrongly influenced by strong events that are independent from climate change, such as strong El Niño events. The KCC method also provides an uncertainty associated with the climate change contribution. We take advantage of this uncertainty to assess the role of internal variability in seasonal forecast and revisit the system skill in predicting it. This new method provides seasonal forecasters with a robust way to properly decompose temperature anomalies into two components, one representing the climate change signal and one reflecting internal variability. It also offers an additional scientific basis to better understand the role of climate change within seasonal forecasting systems.</p>","PeriodicalId":50734,"journal":{"name":"Atmospheric Science Letters","volume":"27 10","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl2.70061","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149099356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-Range Dependence, Multifractality, and Trends of Drought Across Multiple Accumulation Periods in Türkiye Derived From SPEI","authors":"Mehmet Ali Çelik","doi":"10.1002/asl2.70055","DOIUrl":"https://doi.org/10.1002/asl2.70055","url":null,"abstract":"<p>Drought is a scale-dependent, memory-driven process, yet its temporal persistence and complexity remain poorly understood relative to its intensity and frequency. This study presents an integrated, scale-aware assessment of drought dynamics across Türkiye using the Standardized Precipitation Evapotranspiration Index (SPEI), derived from ERA5-Land precipitation and potential evapotranspiration data spanning 1975–2022. Monthly SPEI series at four accumulation scales (1, 3, 6, and 12 months) were analyzed using Detrended Fluctuation Analysis (DFA) and Multifractal DFA (MFDFA) to quantify persistence and complexity, complemented by ordinary least squares regression, the Mann–Kendall test, and Sen's slope estimator to assess trend direction, significance, and magnitude. DFA scaling exponents increased systematically from near-random values (<i>α</i> = 0.49–0.59) at SPEI-1 to strongly persistent, memory-dominated dynamics (<i>α</i> = 1.06–1.23) at SPEI-12, while MFDFA revealed a parallel intensification of multifractal complexity, with spectrum widths (Δ<i>α</i>) expanding from 0.03–0.20 to 0.21–0.65 across the same range of scales. Trend analyses uncovered spatially limited and largely insignificant drying at short time scales, evolving into widespread, statistically significant negative trends (<i>p</i> &lt; 0.05) at SPEI-6 and SPEI-12, with the steepest declines identifying several basins as persistent long-term drought hotspots, while only one basin exhibited a significant wetting trend. These findings establish that drought in Türkiye is governed by scale-dependent persistence and multifractal heterogeneity rather than short-term randomness, underscoring the inadequacy of short-timescale indices for long-term risk assessment and highlighting the need for persistence- and complexity-informed drought monitoring frameworks.</p>","PeriodicalId":50734,"journal":{"name":"Atmospheric Science Letters","volume":"27 9","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl2.70055","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148994199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mediterranean Warming Amplified the Convective Environment During the December 13, 2024 Severe Thunderstorm at Rome–Fiumicino Airport","authors":"Tommaso Alberti,&nbsp;Davide Faranda","doi":"10.1002/asl2.70060","DOIUrl":"https://doi.org/10.1002/asl2.70060","url":null,"abstract":"<p>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.</p>","PeriodicalId":50734,"journal":{"name":"Atmospheric Science Letters","volume":"27 9","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl2.70060","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148860151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Deep Learning Model for Decadal Indian Ocean Dipole","authors":"Sitraka Ny Aina Raharivelo,&nbsp;Yanyan Huang,&nbsp;Danwei Qian,&nbsp;Jing-Jia Luo,&nbsp;Peishu Zong","doi":"10.1002/asl2.70053","DOIUrl":"https://doi.org/10.1002/asl2.70053","url":null,"abstract":"<p>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.</p>","PeriodicalId":50734,"journal":{"name":"Atmospheric Science Letters","volume":"27 8","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl2.70053","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148753470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Damaging Surface Hail in Simulations of Satellite-Detected Hailstorms in Australia's Tropics","authors":"Timothy H. Raupach,&nbsp;Sarah D. Bang,&nbsp;John T. Allen","doi":"10.1002/asl2.70058","DOIUrl":"https://doi.org/10.1002/asl2.70058","url":null,"abstract":"<p>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.</p>","PeriodicalId":50734,"journal":{"name":"Atmospheric Science Letters","volume":"27 8","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl2.70058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148752863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Well Is the Lake-Land Breeze Circulation of Lake Victoria Captured in ECMWF Operational Analysis?","authors":"Musa Ssemujju,&nbsp;Marlon Maranan,&nbsp;Andreas H. Fink,&nbsp;Simon Ageet","doi":"10.1002/asl2.70059","DOIUrl":"https://doi.org/10.1002/asl2.70059","url":null,"abstract":"<p>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.</p>","PeriodicalId":50734,"journal":{"name":"Atmospheric Science Letters","volume":"27 8","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl2.70059","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148752736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Index to Characterize the South Indian Ocean High-Pressure System and Its Variability","authors":"Kwesi Akumenyi Quagraine,&nbsp;Kwesi Twentwewa Quagraine,&nbsp;Francis Nkrumah,&nbsp;Bruce Hewitson,&nbsp;Mark Tadross,&nbsp;Nana Ama Browne Klutse","doi":"10.1002/asl2.70056","DOIUrl":"https://doi.org/10.1002/asl2.70056","url":null,"abstract":"<p>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.</p>","PeriodicalId":50734,"journal":{"name":"Atmospheric Science Letters","volume":"27 8","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl2.70056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148667476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}