Earth and Space Science最新文献

{"title":"Broadband Seismic Source Characterization Based on Composite Source Time Functions: A Case Study of the 2022 Luding Earthquake","authors":"Wenjing Wang,&nbsp;Hong Zhou,&nbsp;Yanan Li,&nbsp;Weijin Xu","doi":"10.1029/2025EA004857","DOIUrl":"10.1029/2025EA004857","url":null,"abstract":"<p>Obtaining broadband ground motion simulations consistent with observed records is essential for seismic modeling, and the key to achieving this lies in a physically reasonable source representation. Only a scientifically constrained broadband source can effectively generate broadband ground motions. This study proposes a broadband source construction method based on composite source time functions within the theoretical Green's function framework. Multiple individual source time functions were combined into a composite function, and the corresponding source parameters were inverted using a simulated annealing algorithm, thereby enabling broadband source characterization in deterministic simulations and achieving broadband ground motion modeling in the 0–40 Hz frequency band. The method was applied to the 2022 Luding Ms 6.8 earthquake. Considering topographic amplification effects on three ground-motion components, response spectra from ten strong-motion stations at near-, intermediate-, and far-field distances were used as constraints to invert for the optimal broadband source parameters. The results indicate that the simulated spatial distribution of peak ground acceleration is generally consistent with the seismic intensity survey released by China's Ministry of Emergency Management (2022, https://www.mem.gov.cn/xw/yjglbgzdt/202209/t20220911_422190.shtml), thereby validating the effectiveness of the proposed approach. Furthermore, quantitative relationships among source time function parameters were established, enabling rapid determination of broadband source parameters and providing a useful reference for similar studies. In summary, the broadband source characterization method developed in this study not only facilitates deterministic broadband ground motion simulation but also incorporates topographic effects and medium properties, offering technical support for broadband ground motion modeling under complex surface conditions.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004857","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Topographical Features of the Lunar Surface Unveiled Through Spherical Geodesic Triangulation Analysis Method of DEM Roughness at Equal Spatial Scales","authors":"Zhengfeng Zhang,&nbsp;Lei Chen,&nbsp;Huai Zhang,&nbsp;Yaolin Shi","doi":"10.1029/2025EA004770","DOIUrl":"10.1029/2025EA004770","url":null,"abstract":"<p>This study introduces an innovative method using equal spherical geodesic triangulation to uniformly sample the digital elevation model (DEM) of the lunar surface, ensuring an even distribution of elevation data. Utilizing spherical spline fitting, we have proposed new methods for calculating slope angles and aspects. An equilateral triangular grid serves as the computational framework to compute the Hurst exponent at various spatial scales, elucidating the lunar surface's 2D spatial characteristics. Elevation statistics indicate that the relatively small areas of lunar maria dominate the peak values of the lunar elevation statistics. This phenomenon is attributed to the early tectonic processes associated with maria. At the kilometer scale, most lunar slopes angle ranges from <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>0</mn>\u0000 <mo>°</mo>\u0000 </mrow>\u0000 <annotation> $0mathit{{}^{circ}}$</annotation>\u0000 </semantics></math> to <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>10</mn>\u0000 <mo>°</mo>\u0000 </mrow>\u0000 <annotation> $10mathit{{}^{circ}}$</annotation>\u0000 </semantics></math>. Meanwhile, at scales from kilometers to several kilometers, slope aspects predominantly exhibit a north–south (NS) orientation. However, this anisotropy is most likely an artefact resulting from satellite data acquisition and DEM processing. We computed 2D Hurst exponents at scales ranging from several kilometers to tens of kilometers. These Hurst exponents demonstrate high resolution in identifying ejecta boundaries of impact craters. These insights contribute to a more comprehensive understanding of the Moon's complex geological history and surface morphology.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004770","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Deciphering Asynchronous Teleconnections: How Dynamic Time Warping Reveals the Hidden Drivers of Iranian Drought","authors":"P. Mahmoudi,&nbsp;P. Jafari,&nbsp;A. Ghaemi,&nbsp;J. Jian,&nbsp;F. Firoozi,&nbsp;J. Yang","doi":"10.1029/2025EA004776","DOIUrl":"10.1029/2025EA004776","url":null,"abstract":"<p>Identifying robust precursors for seasonal drought is a central challenge in Earth system science, traditionally approached with linear methods that often fail to capture the complex, asynchronous nature of teleconnections. These methods, by assuming fixed-phase relationships, can overlook or misrepresent crucial climate drivers. This study introduces Dynamic Time Warping (DTW) as a powerful diagnostic framework to overcome this limitation by quantifying similarity between time series irrespective of temporal misalignments. We apply this methodology to investigate the lagged relationships between 19 large-scale climate patterns and seasonal drought variability, derived from the Standardized Precipitation Index, across 13 distinct climatic zones in Iran (1994–2022). Our analysis reveals a significant paradigm shift in understanding Iran's drought drivers. The Western Hemisphere Warm Pool (WHWP), an often-overlooked predictor, emerges as the most dominant and widespread precursory signal, exhibiting statistically significant lead times of up to two seasons (6 months) for over 75% of the country. This contrasts sharply with the conventionally accepted roles of El Niño-Southern Oscillation and North Atlantic Oscillation. The DTW framework also effectively identifies regions of multiple teleconnection influences (“climatic crossroads”) and areas where local dynamics prevail (“silent zones”). Our findings demonstrate that time-adaptive modeling is essential for uncovering hidden drivers in climate systems, offering a new pathway to enhance the physical basis and predictive skill of seasonal forecasting models. This approach provides a transferable methodology for reassessing climate teleconnections globally.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004776","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Refine the Uncertainty of GPM IMERG Precipitation Product Accounting for the Inherent Error From Rain Gauges Estimations","authors":"Yue Li,&nbsp;Bowei Han,&nbsp;Lin Chen,&nbsp;Renjun Zhou,&nbsp;Rui Li","doi":"10.1029/2025EA004745","DOIUrl":"10.1029/2025EA004745","url":null,"abstract":"<p>Satellite precipitation retrieval accuracy assessment requires reliable ground validation, yet conventional approaches using rain gauges as “truth” neglect representativeness errors inherent in point-to-area approximations. This study uses 7,253 rain gauges (2020–2024) over the Jianghuai monsoon region to quantify these errors and reassess Integrated Multi-satellite Retrievals for GPM (IMERG) performance. We show that at least 16 gauges per 0.2° grid are required for reliable area-mean precipitation estimates. Analysis reveals dual dependence of gauge representativeness errors on gauge density (n, number of gauges per grid cell) and rainfall intensity (RR): (a) errors decay exponentially with increasing n, following root mean square error (RMSE) = ae^−bn, where a and b are fitted coefficients; (b) errors increase with RR when n is held constant. Parameterized relationships enable error quantification across density gradients. Direct IMERG-gauge comparisons show that seasonal mean differences are negatively correlated with gauge density (Pearson's <i>r</i> = −0.33, <i>p</i> &lt; 0.01), indicating that sparse gauge networks are a primary driver of apparent discrepancies. Error decomposition using gauge uncertainties yielded bounded IMERG retrieval errors (RMSE^<i>B</i>_min/max). Applying the same framework to Kling-Gupta efficiency (KGE) revealed similarly improved IMERG performance after removing gauge-induced uncertainties, reinforcing the internal consistency of our analysis. Crucially, incorporating gauge errors reduced significant discrepancy frequency by 16%/6%/16%/17% across seasons, proving that traditional methods overestimate IMERG-gauge deviation occurrence by 6%–17%. This establishes gauge density as critical accuracy determinant, provides robust error-quantification framework, and reveals that terrain-complexity misinterpretations arise when disregarding representativeness errors, with implications for global satellite precipitation validation.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004745","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Capturing Mesoscale and Submesoscale Ocean Fronts in the Gulf of Mexico With Gaussian Mixture Modeling and Satellite Observations","authors":"Ethan Cruz,&nbsp;Bulusu Subrahmanyam","doi":"10.1029/2025EA004855","DOIUrl":"10.1029/2025EA004855","url":null,"abstract":"<p>This study advances the detection of ocean fronts in the Gulf of Mexico (GoM) by comparing traditional front detection algorithms with a machine learning model. Specifically, we evaluate the performance of three widely used methods, Canny Edge Detection (referred to as Canny), the Cayula-Cornillon Algorithm (CCA) (referred to as CCA), and the Belkin-O’Reilly Algorithm (referred to as BOA), against a machine learning–based Gaussian Mixture Model (referred to as GMM). These methods are applied to a suite of satellite-derived oceanographic variables, including Sea Surface Temperature (SST), Sea Surface Salinity (SSS), Chlorophyll-a (Chl-a), and Absolute Dynamic Topography (ADT). To distinguish mesoscale from submesoscale features, we incorporate high-resolution data sets from the Surface Water and Ocean Topography (SWOT) mission and the NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. The algorithms are tested through case studies capturing a range of oceanographic conditions, including seasonal variations, flood and drought events, and different phases of the Loop Current (LC). The GMM approach offers a statistical, machine-learning based alternative to traditional gradient- and histogram-based methods. By benchmarking these techniques, this study provides a comprehensive assessment of their strengths and limitations in identifying dynamic frontal structures. These features are key to understanding vertical and lateral exchanges of heat, nutrients, and carbon, and play a critical role in regional marine ecosystems and climate processes.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004855","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Dataset of Quiet Space Weather Periods for Ionospheric Studies","authors":"Šimon Mackovjak,&nbsp;Silvia Kostárová,&nbsp;Jaroslav Chum,&nbsp;Carsten Schmidt,&nbsp;Patrick Hannawald,&nbsp;Sabine Wüst,&nbsp;Lisa Küchelbacher,&nbsp;Vladimír Truhlík,&nbsp;Petra Koucká Knížová,&nbsp;Jaroslav Urbář,&nbsp;Lukáš Randuška,&nbsp;Filip Štempel,&nbsp;Ján Kubančák","doi":"10.1029/2025EA004537","DOIUrl":"10.1029/2025EA004537","url":null,"abstract":"<p>The ionosphere is a dynamic environment regularly affected from above and from below. This study identifies periods within the years 2000–2023 when the impact from above, driven by space weather, was minimal. The quiet space weather periods have wide usage for two types of ionospheric studies. At first, studies of isolated space weather events that disrupt quiet periods. Second, studies of the lower atmosphere effects on the ionosphere when space weather drivers are negligible. For the first time, we provide examples of both such studies by using data from GNSS receivers, a continuous Doppler sounding system, ionosondes, and airglow spectrometers. The results demonstrate the capability of our data set to contribute to an extensive effort to provide interpretations to still unexplained ionospheric variations.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004537","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 Bayesian Approach to F-Region Mesoscale Flow Estimation With EISCAT_3D","authors":"Mizuki Fukizawa,&nbsp;Yasunobu Ogawa,&nbsp;Koji Nishimura,&nbsp;Genta Ueno,&nbsp;Takanori Nishiyama,&nbsp;Taishi Hashimoto,&nbsp;Takuo T. Tsuda","doi":"10.1029/2025EA004827","DOIUrl":"10.1029/2025EA004827","url":null,"abstract":"<p>The ionospheric electric field is a key parameter for understanding ionospheric electrodynamics and the magnetosphere–ionosphere coupling. Several methods have been developed to reconstruct the two-dimensional distribution of the ionospheric electric field from line-of-sight (LOS) ion velocities observed by incoherent scatter radars. Approaches tailored to the upcoming tri-static incoherent scatter radar system, EISCAT_3D (E3D), have also been proposed. In this study, we propose a new method to reconstruct mesoscale flows using a Bayesian estimation. We applied maximum a posteriori estimation to reconstruct shear flow fields with maximum velocities of 1,000 m/s at 200 km altitude. The electric field was then estimated under the assumption of <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>E</mi>\u0000 <mo>×</mo>\u0000 <mi>B</mi>\u0000 </mrow>\u0000 <annotation> $boldsymbol{E}times boldsymbol{B}$</annotation>\u0000 </semantics></math> drift. The reconstructed shear flows showed root-mean-square errors (RMSEs) of 57–101 m/s in the ion velocity and 3–5 mV/m in the electric field. Typical mesoscale flow structures were reconstructed with errors of less than 100 m/s within about 150–200 km centered on the magnetic zenith. These results demonstrate the feasibility of resolving mesoscale ionospheric structures. Our method will be extended to reconstruct electric current structures in future studies.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004827","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Do the Wettest Days Occur Together? A Global Analysis on Disentangling Precipitation Intensity From Seasonal Timing","authors":"Saurav Bhattarai,&nbsp;Nawa Raj Pradhan,&nbsp;Rocky Talchabhadel","doi":"10.1029/2025EA004845","DOIUrl":"10.1029/2025EA004845","url":null,"abstract":"<p>Current precipitation analysis focuses on extreme events or total amounts but misses a critical question: when does the majority of precipitation occur during the year? We introduce a framework that separates two fundamental aspects of precipitation patterns: how many of the wettest individual days contribute to annual totals versus what is the minimum number of consecutive days required to reach the same totals. Using ERA5 data spanning 1980–2024 over global land surfaces, we first compute multi-threshold indices for 25%, 50%, and 75% of annual precipitation through both approaches—selecting the wettest days scattered throughout the year (WD25, WD50, WD75) and then find the shortest consecutive periods (WD25R, WD50R, WD75R). Results show these two dimensions evolve independently: notably, the Amazon Basin shows 15%–18% fewer days needed through both approaches (more concentrated and more consecutive), while continental regions like eastern North America show 12%–25% increases (more scattered and less consecutive). Monsoon regions demonstrate strong alignment between wettest days and consecutive periods (concentrated rainy seasons), while mid-latitude regions show large misalignments (scattered patterns). These findings demonstrate that identical changes in precipitation intensity can produce opposite changes in seasonal timing—a distinction critical for flood risk, drought duration, and water storage that traditional extreme event indices cannot capture.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004845","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147682974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Mechanisms of MCS Initiation and Maintenance During Extreme Rainstorm Events in Semi-Arid Regions: A Case Study of Qingyang","authors":"Baolong Shi,&nbsp;Zhiyi Wang,&nbsp;Yue Su,&nbsp;Jingjie Wang,&nbsp;Tianbei Wu,&nbsp;Jinyan Wang,&nbsp;Yanzhen Kang","doi":"10.1029/2025EA004697","DOIUrl":"10.1029/2025EA004697","url":null,"abstract":"<p>Extreme rainstorm events are becoming more frequent in semi-arid regions, yet the mechanisms behind their development and maintenance, especially from dynamical and thermal perspectives, which remain insufficiently quantified, limiting forecasting capabilities. This study employs the WRF model to investigate an extreme rainstorm case in a semi-arid valley region. Results show that the rainstorm was significantly influenced by the northward extension of the Western Pacific Subtropical High (WPSH) and a low pressure system. The onset of the Mesoscale Convective System (MCS) was facilitated by moist-unstable stratification, valley wind circulation, and strong terrain-induced vertical motion. During the mature stage of the MCS, a complex interplay of dynamic systems and unique trumpet-shaped valley topography sustained the extreme rainfall. The interaction between orographically modified valley winds and a persistent low-level jet (LLJ) formed a strong convergence zone, characterized by a LLJ-left shear line, intensified surface convergence, and enhanced northerly flows, which increased positive vorticity. Vorticity budget analysis revealed that vorticity advection and divergence effects were the dominant contributors to vorticity generation, emphasizing the importance of low-level convergence and spin transport in maintaining the MCS. In parallel, strong diabatic heating from moist air ascent created a positive feedback loop that further energized convection. The valley's topography acted as a key amplifier by concentrating moisture and enhancing vertical motion. These findings highlight the critical role of terrain-induced dynamics in sustaining extreme rainfall in semi-arid environments, offering valuable insights for improving heavy rain forecasts in vulnerable regions.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004697","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147682998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Prospects for Arctic Summertime Sea Ice Prediction Based on Arctic Seasonal Prediction System (ArcSPS)","authors":"Zhongxiang Tian,&nbsp;Xi Liang,&nbsp;Dakui Wang,&nbsp;Zhuoming Ding,&nbsp;Fu Zhao,&nbsp;Ming Li,&nbsp;Na Liu,&nbsp;Jiaying Huang","doi":"10.1029/2025EA004828","DOIUrl":"10.1029/2025EA004828","url":null,"abstract":"<p>To satisfy the needs of the Arctic sea ice seasonal prediction in summer, we developed the Arctic Seasonal Prediction System (ArcSPS). This system integrates an Arctic sea ice–ocean–atmosphere coupled model with an ensemble-based Kalman Filter data assimilation model. The data assimilation model has a capacity of assimilating sea ice concentration, sea ice thickness, and sea surface temperature (SST) observations simultaneously into the coupled model state, providing an optimal state estimate at prediction onset. The mean September Integrated Ice Edge Error (IIEE) in the Arctic Ocean from totally 180 prediction runs, initialized on the 1st day of June, July, and August during 2013–2022, are 1.53 × 10⁶ km², 1.4 × 10⁶ km² and 1.32 × 10⁶ km², respectively, which are lower than those of most dynamic models reported in Bushuk et al. (2024), https://doi.org/10.1175/bams-d-23-0163.1, indicating that the ArcSPS has a promising performance on the September sea ice prediction at lead times of 1–3 months. The predicted sea ice evolutions in summertime are basically consistent with the observations regarding both spatial patterns and total metrics. The predicted September sea ice edge and thickness distributions agree well with the observations. To further improve seasonal sea ice prediction, efforts should be concentrated on assimilating more observational variables and utilizing more reasonable air‒ice‒ocean interaction representations in high-resolution models.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004828","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}