International Journal of Climatology最新文献

{"title":"Spatiotemporal Evolution of Hydroclimatic Variables in the Brazilian Semi-Arid Region Through the Aridity Index and Susceptibility to Desertification","authors":"Ronaldo Guilherme Santos Lima,&nbsp;Izaias Rodrigues de Souza Neto,&nbsp;André Quintão de Almeida,&nbsp;Vania Elisabete Schneider,&nbsp;Ludmilson Abritta Mendes","doi":"10.1002/joc.70383","DOIUrl":"https://doi.org/10.1002/joc.70383","url":null,"abstract":"<p>Climate change intensifies temperatures and alters precipitation patterns, impacting water availability and increasing desertification. This article assesses the spatiotemporal evolution of the Brazilian semi-arid region (1961–2020) using the aridity index (AI). It investigates susceptibility to desertification and the behaviour of climatic variables influencing these processes. The study covers the Brazilian Northeast (NEB) and the states of Minas Gerais and Espírito Santo, which are also affected by the region's overall spatial patterns with regions with similar climatic patterns. The climatic variables analysed during the period from 1961 to 2020, based on Brazilian Daily Weather Gridded Data (BR-DWGD), were: maximum air temperature (<i>T</i>_max), minimum air temperature (<i>T</i>_min), precipitation (<i>P</i>), potential evapotranspiration (ET) and the Thornthwaite aridity index. The Mann–Kendall test was used for trend analysis, in combination with land-cover analysis of satellite imagery. The temporal analysis revealed a statistically significant trend of warming and increased aridity in the region. There is an observed expansion of areas where <i>T</i>_max exceeds 31°C and <i>T</i>_min exceeds 19°C, associated with increased ET and reduced <i>P</i>. The conversion of native vegetation into agricultural areas, linked to rising ET, is evident and warrants further investigation regarding the crops implemented over time. Seasonal analysis of the series and investigation of extreme events, as well as ocean variability, are also recommended as modulating factors of regional climatic changes.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 8","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.70383","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148269236","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":"Alaskan Ridge Blocking and Associated Winter Cold Conditions Over North America","authors":"Varunesh Chandra,&nbsp;James E. Overland,&nbsp;Muyin Wang","doi":"10.1002/joc.70374","DOIUrl":"https://doi.org/10.1002/joc.70374","url":null,"abstract":"<p>Atmospheric blocking over the northern North Pacific–Alaska sector has a central role in shaping winter weather variability and cold-air outbreaks across central and eastern North America. Motivated by recent high-impact Alaskan ridge events, this study examines the climatological characteristics of Alaskan atmospheric blocking and its downstream temperature response based on reanalysis data during January–February (JF) 1979–2023. The meridional gradient of potential vorticity (PVy) is used here as a physically motivated dynamical index in which a reduced PVy is associated with zonal wind reversal and weakened westerly winds and conditions favourable for ridge amplification. The PVy index exhibits spatial structures and temporal evolution similar to the traditional Tibaldi–Molteni blocking index. Negative-PVy anomalies over the Bering Sea occur in most winters, typically persisting for several days to one week. Composites based on negative PVy show a robust atmospheric circulation pattern characterised by enhanced ridging over Alaska and a downstream trough over North America, accompanied by negative near-surface temperature anomalies over the central and eastern United States and positive anomalies over Alaska and the Pacific Arctic. Although negative-PVy conditions are common in winter, prolonged blocking episodes spanning much of a month are rare, consistent with the transient nature of blocking events. Selected winters (1979, 1986, 1988 and 2018) are illustrative case studies that demonstrate the range of circulation structures and surface-temperature responses, embedded within a long-term climatological relationship. These results highlight the important meteorological role of Alaskan blocking and identify PVy as a simple, physically interpretable diagnostic of background-flow conditions associated with North American winter temperature variability.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 8","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.70374","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148268796","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":"Potential Causes of Anti-Phase Summer Precipitation Variability Between the Middle and Lower Reaches of the Yangtze River","authors":"Yuwei Zhou,&nbsp;Ge Liu,&nbsp;Xiaolu Yan,&nbsp;Sulan Nan,&nbsp;Ting Zhang,&nbsp;Yinghan Sang,&nbsp;Xuefeng Han,&nbsp;Yuhan Feng,&nbsp;Hancheng Zou","doi":"10.1002/joc.70373","DOIUrl":"https://doi.org/10.1002/joc.70373","url":null,"abstract":"<div>\u0000 \u0000 <p>Summer precipitation in the middle and lower reaches of the Yangtze River generally shows synchronous variability and is thus extensively studied as a unified climatic region. However, out-of-phase variations occur between the middle and lower reaches in some years. This study investigates the mechanisms of the positive middle Yangtze River precipitation (MYRP)–negative lower Yangtze River precipitation (LYRP) pattern from the perspectives of atmospheric circulation and land-ocean thermal anomalies. The results suggest that a non-canonical Silk Road Pattern (SRP) teleconnection in the upper troposphere, coupled with a mid-to-lower tropospheric anomalous anticyclone over Northeast Asia and a weakened western Pacific subtropical high (WPSH), contributes to this precipitation pattern. Further analysis reveals that colder-than-normal land thermal anomalies in the Greater Caucasus Mountains and the northeastern Tibetan Plateau, as well as warmer-than-normal sea surface temperature anomalies (SSTAs) in the Sea of Japan, may help maintain the SRP-like Rossby wave train (SLWT), therefore influencing the positive MYRP–negative LYRP pattern. Linear baroclinic model sensitivity experiments further support the identified thermal anomalies can excite and maintain the SLWT. Given that the SLWT differs to some extent from the classical SRP in both wave source and downstream structure, this study also proposes a SLWT index based on 200-hPa vorticity anomalies. This index effectively captures both the spatial structure of the SLWT and its link with out-of-phase precipitation anomalies between the middle and lower reaches of the Yangtze River and may serve as a potential indicator for the occurrence probability of the positive MYRP–negative LYRP pattern. These findings may improve our understanding of regional precipitation mechanisms in the Yangtze River basin, thereby providing a scientific basis for improved disaster prevention and mitigation strategies.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 8","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148269214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transition in Köppen Climate Zones and Its Impacts on Hydroclimatic Extremes Across India","authors":"Arpit Tiwari,&nbsp;Preethi Nanjundan,&nbsp;Ravi Ranjan Kumar,&nbsp;Satyaban Bishoyi Ratna","doi":"10.1002/joc.70381","DOIUrl":"https://doi.org/10.1002/joc.70381","url":null,"abstract":"<div>\u0000 \u0000 <p>Shifting climatic zones across India are reshaping the country's hydroclimatic balance, with significant consequences for drought behaviour and water security. This study examines how spatial changes in Köppen–Geiger climate zones between two climatological periods (1961–1990 and 1991–2020) are influencing long-term drought characteristics. Using high-resolution gridded rainfall and temperature data from the India Meteorological Department, the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI) are used to assess drought intensity and extent across five major climate categories: tropical, arid, temperate, continental and polar. Results reveal a noticeable expansion of the arid zone by 3.86% and a contraction of the temperate zone by 6.94%, indicating a transition toward warmer and drier climates. These spatial shifts have altered regional drought behaviour, with formerly moderate zones experiencing more frequent and intense droughts. The arid and tropical zones, where expansion is observed, show increasing drought severity, largely driven by rising evapotranspiration due to temperature increases of 0.12°C–0.25°C/decade (<i>T</i>_max) and 0.10°C–0.20°C/decade (<i>T</i>_min). In contrast, regions where the temperate climate is receding are showing a loss of climatic buffering capacity against drought. SPEI captures more widespread and severe drought events than SPI, underscoring the increasing role of thermal stress in water balance anomalies. This study highlights that changes in the spatial extent of climate zones are a key driver of evolving drought patterns in India. Recognising these shifts is essential for improving temperature-sensitive drought monitoring and formulating zone-specific adaptation strategies in the face of accelerating climate change.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 8","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148269223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reproduction of Indian High Temperature Patterns: A CMIP6 Model Evaluation","authors":"Ganaraj Dalal,&nbsp;Shushobhit Chaudhary,&nbsp;Vittal Hari","doi":"10.1002/joc.70391","DOIUrl":"https://doi.org/10.1002/joc.70391","url":null,"abstract":"<div>\u0000 \u0000 <p>High temperature (HT) over India has garnered increasing attention in recent years due to their substantial impact on human health and well-being. Given their growing significance, extensive efforts have been made to understand the driving mechanisms behind these events, as well as their projected changes under future climate scenarios using global climate models (GCMs). However, confidence in such projections depends critically on how well GCMs can replicate historical climate behaviour. In this study, we evaluate the performance of models participating in Phase 6 of the Coupled Model Intercomparison Project (CMIP6) in capturing the spatio-temporal characteristics of HT over India. Observational data reveal two distinct patterns: (i) an increasing trend in HT over southwestern India (SWI), and (ii) a pronounced east–west asymmetry over northern India, characterised by more frequent HT in the northwest and a decline in the east. The SWI HT pattern is closely linked to the El Niño–Southern Oscillation, which is reasonably well represented by the CMIP6 models. In contrast, the models fail to reproduce the observed asymmetry in northern India, likely due to their inadequate simulation of the large-scale atmospheric response to the Atlantic Niño. These findings underscore the importance of rigorous model evaluation before relying on CMIP6 projections to inform HT-related adaptation and policy strategies in a highly vulnerable region like India.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 8","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148268971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving CWRF Prediction of Summer Monthly Precipitation Over the Yangtze River Basin With Spatio-Temporal Graph Neural Network","authors":"Tao Li,&nbsp;Han Wu,&nbsp;Fang Wang,&nbsp;Shenjun Zhong,&nbsp;Jianjun Xue","doi":"10.1002/joc.70375","DOIUrl":"https://doi.org/10.1002/joc.70375","url":null,"abstract":"<div>\u0000 \u0000 <p>Accurate summer precipitation forecast over the Yangtze River Basin (YRB) is crucial for flood early warning and effective regional water resource management. The Climate-Weather Research and Forecasting (CWRF) model is a useful tool for providing across-season monthly precipitation prediction during flooding season in the YRB, but it still exhibits notable limitations in accurately capturing precipitation variations both spatially and temporally. To alleviate these limitations, a novel deep learning framework utilising a spatio-temporal graph neural network (GNN) is proposed to improve the prediction skill of CWRF. The result suggests that the proposed GNN model outperforms the existing neural network-based models across multiple evaluation metrics on precipitation prediction over the YRB. Specifically, GNN achieves the most substantial reduction in root-mean-square error across the YRB. It also outperforms other models in terms of temporal correlation coefficient, with overall monthly increases (exceeding 0.1 in June) compared to the raw CWRF output. In terms of anomaly correlation coefficient, GNN shows obvious enhancements, indicating better year-to-year consistency. These findings provide valuable guidance for enhancing precipitation forecasts, particularly in regions characterised by complex topography, irregular spatial domains, and diverse climate conditions.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 8","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148269213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Projected Annual and Monsoonal Precipitation Trends of CMIP6 Over Peninsular Malaysia","authors":"Nurul Afiqah Mohamad Arbai,&nbsp;Masayasu Irie","doi":"10.1002/joc.70335","DOIUrl":"https://doi.org/10.1002/joc.70335","url":null,"abstract":"<p>In this study, we investigated the historical and projected precipitation trends over Peninsular Malaysia (PM) using ground-based precipitation records and high-resolution CMIP6 GCMs from NEX-GDDP-CMIP6. Long-term records from 518 reliable gauges were analysed for 1973–2022 to understand past spatial and monsoonal precipitation trends. Ten GCMs were assessed and bias-corrected using a linear scaling method, with the five best-performing models selected to construct a multi-model ensemble (MME). Future trends for 2051–2100 were evaluated under the SSP2-4.5 and SSP5-8.5 scenarios. The results indicate a spatially heterogeneous distribution of precipitation, which is heavily influenced by topography and monsoonal regimes. Historically, negative trends have dominated the Southwest Monsoon (SWM). Meanwhile, positive trends have been observed during the Northeast Monsoon (NEM), particularly along the east coast. Under SSP2-4.5, the future trends showed modest increases and smaller negative areas. Meanwhile, more widespread and intense declines in precipitation were projected for SSP5-8.5, particularly along the southeastern coast. These findings highlight the climatic sensitivity of PM under varying emission pathways and emphasise the importance of integrating reliable observational data and robust model ensembles for future water resource planning and climate adaptation strategies.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 7","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.70335","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148247823","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":"On the Temporal Variability of Precipitation in Iraq: Arid-Wet Years and Extreme Events","authors":"Ali Raheem Al-Nassar,&nbsp;Josep L. Pelegrí,&nbsp;Pánfilo Masciángioli","doi":"10.1002/joc.70350","DOIUrl":"https://doi.org/10.1002/joc.70350","url":null,"abstract":"<p>Here we examine the variability of precipitation in Iraq, focusing on the differences between arid and wet years as well as on the intensity of extreme events. This is done analysing several long precipitation records—84 years of monthly precipitation in four stations (1938–2023, except 2003 and 2004) and 19 years of daily precipitation data (2005–2023) in the Baghdad station—together with reanalysis weather data. The long time series gives annual (mean ± standard deviation) precipitation values of 367 ± 140, 107 ± 59, 138 ± 65 and 136 ± 60 mm in Mosul, Rutba, Baghdad and Basrah, respectively, with a weighted mean of 182 ± 57 mm for the entire country. The time series are dominated by seasonality, with maximum winter and negligible summer precipitation, and one-order-of-magnitude interannual variations. An annual-precipitation probability density function distinguishes wet and arid years—above and below the 25 and 75 percentiles, respectively—with substantial differences in the seasonal cycle. The monthly precipitation is significantly correlated with the Indian Ocean Dipole (IOD) index, suggesting that the autumn-winter arrival of moisture from the Red Sea, Arabian Sea and Persian Gulf enhances precipitation. Combining the Baghdad daily record with weather reanalysis data allows identifying 36 extreme precipitation events that are classified as jet streak, cut-off low, upper-air trough or Rex block events. These episodes account for 1452 mm of precipitation, or 56% of the total for the 2005–2023 period, but do not increase their frequency during wet years, hence suggesting that the ultimate cause for the arid-wet year variability is the seasonal IOD conditioning. Finally, an extreme value analysis for both the daily and monthly data—with both peak over threshold (POT) and block maxima (BM) methods—provides return values for periods up to 100 years. For daily data, both methods give similar mean values but POT provides much narrower high-confidence bands; for monthly data, both methods give similar mean and high-confidence values.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 7","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.70350","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148247824","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":"Solar Radiation–Driven Machine Learning for Modelling Reference Evapotranspiration Using ERA5-Land in a Semi-Arid Microclimatic Basin in Türkiye","authors":"Mehmet Ali Çelik,&nbsp;Ahmed Elbeltagi","doi":"10.1002/joc.70344","DOIUrl":"https://doi.org/10.1002/joc.70344","url":null,"abstract":"<div>\u0000 \u0000 <p>Accurate estimation of reference evapotranspiration (ETo) is critical for effective water resource management, irrigation planning, and climate adaptation, particularly in semi-arid regions where water scarcity and climatic variability are pronounced. This study assessed the performance and temporal stability of four machine learning (ML) algorithms [Multilayer Perceptron (MLP), Random SubSpace (RSS), M5P model tree (M5P), and Random Forest (RF)] in estimating daily ET in the Iğdır Basin, one of eastern Türkiye's most productive yet hydrologically vulnerable agricultural zones. Using ERA5-Land reanalysis data, the models were trained and validated across two distinct periods (1950–1999 and 2000–2024) to evaluate both historical accuracy and robustness under changing climatic conditions. Solar radiation (SR) was identified as the primary driver of ETo, highlighting the dominant role of radiative energy in modulating evapotranspiration variability, even under the predominantly water-limited conditions of the basin's semi-arid environment. A near-perfect correlation between ETo and SR confirmed the dominant influence of solar energy on evaporative demand. Among the tested models, M5P and MLP achieved the highest predictive accuracy and maintained consistent performance across both periods, indicating strong generalizability and resistance to climatic non-stationarity. In contrast, RS and RF exhibited higher error rates and reduced sensitivity to nonlinear interactions, limiting their applicability in dynamic environmental conditions. These results emphasise the ecological and hydrological relevance of energy-based modelling approaches for drought-sensitive regions. The integration of ERA5-Land data with machine learning provides a scalable and data-efficient alternative to conventional ETo estimation methods, particularly where in situ measurements are limited. The proven accuracy and stability of the M5P and MLP models offer a reliable foundation for long-term hydrological forecasting, adaptive irrigation planning, and climate resilience efforts in eastern Türkiye's agricultural landscapes.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 7","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148247819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance Evaluation of the MPAS Model in Simulating Southeast Asian Rainfall Characteristics","authors":"Nguyen Thanh Hung,&nbsp;Alugula Boyaj,&nbsp;Srivatsan V. Raghavan,&nbsp;Nguyen Ngoc Son,&nbsp;Bhenjamin Jordan Ona","doi":"10.1002/joc.70343","DOIUrl":"https://doi.org/10.1002/joc.70343","url":null,"abstract":"<p>Southeast Asia's (SEA) complex monsoon climate is highly vulnerable to extreme weather, necessitating robust atmospheric models for improved forecasting. This study evaluates the performance of the next-generation Model for Prediction Across Scales–Atmosphere (MPAS) in simulating seasonal rainfall and atmospheric dynamics over SEA. We conducted a continuous MPAS simulation with uniform 10 km horizontal cell spacing from 2000 to 2020, forced by ERA5 reanalysis and validated outputs against multi-source weighted-ensemble precipitation (MSWEP) observed precipitation (10 km) and ERA5 reanalyses. The model captures the north–south rainfall gradients and the spatial–temporal characteristics of seasonal rainfall, transitions, wind reversals and moisture transport with high fidelity over northern continental regions. It also captures the timing and intensity of peak rainfall. An Empirical Orthogonal Function analysis further shows that MPAS effectively represents the dominant rainfall variability modes associated with ENSO and IOD, though with slightly weaker amplitudes. However, a persistent wet bias is evident across the Maritime Continent, marked by the overestimation of high-intensity rainfall events. Despite these specific biases, MPAS effectively captures the core features of the SEA monsoons, highlighting its potential as a powerful tool for regional climate simulation. Continued refinement of convection and microphysics schemes, together with increased model resolution, could further enhance its performance for both research and operational applications over SEA.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"46 7","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.70343","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148247770","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}