International Journal of Climatology最新文献

{"title":"Indian Summer Monsoon Rainfall Characteristics Derived From Multiple Gridded Precipitation Datasets: A Comparative Assessment","authors":"Sandipan Paul,&nbsp;Priyank J. Sharma,&nbsp;Ramesh S. V. Teegavarapu","doi":"10.1002/joc.8708","DOIUrl":"https://doi.org/10.1002/joc.8708","url":null,"abstract":"<div>\u0000 \u0000 <p>Precipitation, a crucial component of the Earth system processes, regulates the spatiotemporal cyclicity of water, energy, and carbon fluxes. Accurate precipitation datasets leverage the understanding of precipitation dynamics and are vital for hydro-climatological studies. South Asian monsoon is a complex, multi-scale interacting, synoptic, and ocean–land–atmosphere coupled system, contributing to significant spatial and temporal variability in summer monsoonal rainfall across India. This study evaluates four types of gridded (observational, satellite, reanalysis, and hybrid) precipitation products in their ability to replicate Indian Summer Monsoonal Rainfall (ISMR) characteristics using the India Meteorological Department (IMD) 0.25° gridded data as the baseline. A comparative assessment is performed in this study that uses several continuous and interval-based performance measures to evaluate the overall rainfall magnitude detectability and time-matched capturing of rainfall events. A new metric, rank score, is developed by aggregating multiple measures to find the best product. The analyses based on several performance measures indicate that MSWEP is the best dataset (rank one) that closely approximates the occurrence and magnitude of IMD-based rainfall events, while APHRODITE, CHIRPS, and IMDAA are ranked as the next best set of products. PGF is ranked the lowest among all products evaluated and is not recommended for applications. Nonetheless, APHRODITE suffers from strong negative biases, while the reanalysis (IMDAA, ERA5-Land, PGF) datasets show significant positive biases. Among the products evaluated, APHRODITE, ERA5-Land, and IMDAA have shown a limited ability to detect excess, normal, and deficit monsoon years, respectively. In general, the performance of satellite-based data products is superior to that of reanalysis datasets in accurately characterising the monsoon years. ERA5-Land is noted to be the best-performing dataset among the reanalysis products. The comprehensive comparative assessment carried out in this study benefits the selection and use of appropriate gridded precipitation products for hydroclimatic modelling, climate variability, and change studies.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143113682","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":"Recent Trends in Extreme Temperature Events Across the Contiguous United States","authors":"Chibuike Chiedozie Ibebuchi,&nbsp;Cameron C. Lee,&nbsp;Scott C. Sheridan","doi":"10.1002/joc.8693","DOIUrl":"https://doi.org/10.1002/joc.8693","url":null,"abstract":"<p>Extreme heat events (EHEs) are becoming prevalent across the globe and are a major factor in terms of temperature-related mortality in the United States (US). In this study, we compare trends in extreme temperature events (ETEs) across the Contiguous US, from 3 reanalysis products, namely: European Centre for Medium-Range Weather Forecasts Reanalysis Version 5 (ERA5), Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA2) and North American Regional Reanalysis (NARR). We focused on the trends (1980–2022) in absolute extreme heat and cold events (ECE) as well as seasonally relative extreme heat and cold events (REHE and RECE). ETEs are defined based on a duration-intensity metric calculated from excess apparent temperature factors, based on the exceedance of apparent temperature beyond local percentile thresholds while incorporating an acclimatisation factor. Our results show that the reanalysis data sets generally produced consistent climatology of ETEs, though with some inconsistencies in their number and spatial distribution. ETE trends in the study region are spatially heterogeneous and were more consistent between MERRA2 and ERA5. Nonetheless, all data sets agree that the frequency of EHEs is significantly increasing in the western parts of the US, whereas REHEs are significantly increasing in the southern parts. The highest increase in the frequency of EHEs occurs in southern California and Nevada, while REHE trends are maximal in Florida. RECEs are significantly decreasing more in spatial scale and magnitude than ECEs, especially towards the coastal regions. The highest decrease in RECEs is in Florida peninsula, southern California and Nevada. The data sets show inconsistency in ECE trends. Trends in excess temperature factors further indicated that extreme cold conditions are decreasing faster compared to the increasing trends of extreme heat conditions. Our findings highlight the need for improving the monitoring of ETEs across the US and for policies that mitigate the impact of ETEs on biological systems.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8693","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143113451","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":"Observed Variability and Future Projections of Urban Heatwaves in Romania","authors":"Sorin Cheval,&nbsp;Vlad Alexandru Amihăesei,&nbsp;Alexandru Dumitrescu,&nbsp;Dana Magdalena Micu,&nbsp;Raluca-Ioana Smău","doi":"10.1002/joc.8714","DOIUrl":"https://doi.org/10.1002/joc.8714","url":null,"abstract":"<div>\u0000 \u0000 <p>The crossroad between built-up areas and extreme heat generates severe consequences on both socio-ecological systems and the natural environment, and the cities are the most vulnerable. The impact is already significant in the present climate and it will be exacerbated under climate change in many regions, including Romania and especially its southern part. The heatwaves (HWs) are a major risk for our cities as they put constant pressure on population, infrastructure and services for several consecutive days. The urban HWs in 41 Romanian cities are analysed in terms of magnitude, amplitude, duration, number and frequency, as well as the variability of the yearly occurrence of the first and last HW events. The study focuses on the warm season (May–September) and refers to the observed variability (1961–2020) and future projections (2021–2050). The main findings reveal that the occurrence of HWs is not conditioned by geographical and climatic conditions and the cities in any region may experience public health risks associated with extreme heat. This requires permanent monitoring of the phenomena, including the present characteristics and estimating future variations according to different scenarios. Considering the increasing frequency and intensity of extreme heat events expected soon, there is a clear need for region-specific adaptation, and policymakers should prioritise strategies to protect vulnerable people.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143113452","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":"Flash Drought Teleconnection With the Large-Scale Climate Drivers in the Homogeneous Rainfall Regions of India","authors":"Akshay Pachore,&nbsp;Renji Remesan,&nbsp;Jayanarayanan Kuttippurath","doi":"10.1002/joc.8711","DOIUrl":"https://doi.org/10.1002/joc.8711","url":null,"abstract":"<div>\u0000 \u0000 <p>Flash drought events can be characterised by the quick depletion of crop root zone soil moisture (rapid intensification) and hence can be termed as agricultural flash droughts. These events can have devastating impacts, such as increasing the risk of agricultural yield loss, heatwaves and increased wildfire risk, which further have cascading impacts on the socio-economic conditions. The regional hotspots of flash droughts are analysed for winter, pre-monsoon, monsoon and post-monsoon seasons over India from 1981 to 2020. We assess the impact of the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on the flash drought frequency (FDF: number of flash drought events). The causal connection of the FDF with the ENSO and IOD is analysed using the PCMCI (Peter and Clark's algorithm combined with the Momentary Conditional Independence) algorithm. The monsoon season (June–September) is found to be more prone to flash droughts with higher spatial/regional average values of total per pixel FDF during the 40-year period over the Central Northeast (~54) and West Central (~41) regions. It is observed that the fraction of the total number of flash droughts during the El Niño years (38.8%) is higher as compared with that in La Niña years (25.7%). It is also found that the co-occurrence of positive/negative IOD with the El Niño phase can alter the seasonal fraction of FDF over India, highlighting the high complexity in the ENSO–IOD interactions. The causal analysis shows that only the Southern Peninsula and West Central regions have significant direct and lagged causal links of average per pixel FDF with IOD. Whereas, similar (direct and lagged) causal connections are observed between the ENSO and IOD. This study reveals that flash droughts and their teleconnections vary greatly among the seasons and regions in India, limiting its accurate predictions and increasing the risk to agricultural communities.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143113453","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":"Tibetan Plateau Vortex Activity and Its Relationship With the Tibetan Plateau Summer Monsoon and Precipitation","authors":"Guantian Wang,&nbsp;Zeyong Hu,&nbsp;Haipeng Yu,&nbsp;Genhou Sun,&nbsp;Weiwei Fan,&nbsp;Ruijia Niu,&nbsp;Bofei Zhang","doi":"10.1002/joc.8713","DOIUrl":"https://doi.org/10.1002/joc.8713","url":null,"abstract":"<div>\u0000 \u0000 <p>The unique topography and location of the Tibetan Plateau (TP) often result in extreme weather events, which have led to disastrous consequences for the TP and its downstream regions. The TP summer monsoon (TPSM) and the TP vortex (TPV) play key roles in the transfer and redistribution of water vapour during the summer months on the TP and are increasingly active in summer and disappear in winter. However, it remains uncertain if a relationship between these systems. Understanding the relationship between these two systems is crucial for uncovering precipitation patterns on the TP, improving weather forecasting accuracy and reducing socioeconomic losses resulting from weather-related disasters. On the basis of GLDAS and ERA5 reanalysis data from 1996 to 2022, the relationships between TPVs and the TPSM were explored in terms of their intensity and spatial characteristics, and their impacts on the spatial distributions of precipitation across the TP were examined in this study. The results indicated that the monthly mean TPSM index agreed very well with the TPV in terms of the annual number formed, duration and intensity, especially in July and August. The investigation of the movement of the center of the TPSM from May to October revealed that the center of the TPSM moves westward when the TPV is active and moves eastward when the TPV is less active. In years with a strong TPSM, the precipitation location generated by TPVs was biased toward the east. This finding could be attributed to the greater number of TPV events and the fact that the TPVs in years with a stronger TPSM moved eastward across a greater distance than those in years with a weaker TPSM. These findings highlightthe contribution of the joint relationship between the TPSM and TPV to seasonal circulation changes and could provide a new perspective for the study and prediction of precipitation distributions on the TP.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143113450","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":"Assessment of Historical and Future Mean and Extreme Precipitation Over Sub-Saharan Africa Using NEX-GDDP-CMIP6: Part I—Evaluation of Historical Simulation","authors":"Sydney Samuel,&nbsp;Gizaw Mengistu Tsidu,&nbsp;Alessandro Dosio,&nbsp;Kgakgamatso Mphale","doi":"10.1002/joc.8672","DOIUrl":"https://doi.org/10.1002/joc.8672","url":null,"abstract":"<div>\u0000 \u0000 <p>This study assesses the performance of 28 NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP-CMIP6) models and their multi-model ensemble (MME) in simulating mean and extreme precipitation across sub-Saharan Africa from 1985 to 2014. The Multi-Source Weighted-Ensemble Precipitation (MSWEP) and Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) are used as reference datasets. Various statistical metrics such as the mean bias (MB), spatial correlation coefficients (SCCs), Taylor skill scores (TSS) and comprehensive ranking index (CRI) are employed to evaluate the performance of NEX-GDDP-CMIP6 models at both annual and seasonal scales. Results show that the NEX-GDDP-CMIP6 can reproduce the observed annual precipitation cycle in all the subregions, with the model spread within observational uncertainties. The MME also successfully reproduces the spatial distribution of mean precipitation, achieving SCCs and TSSs greater than 0.8 across all subregions. The biases in mean precipitation are consistent across different reference datasets. However, most of the NEX-GDDP-CMIP6 models show trends of mean precipitation opposite to observations. While the MME can generally reproduce the spatial distribution of extreme precipitation, its performance varies with the reference dataset, particularly for the number of rainy days (RR1) and maximum consecutive dry days (CDD). TSS values for extreme precipitation indices differ significantly by region, reference data and index, with the lowest values over South Central Africa and the highest over West Southern Africa. The CRI indicates that no single model consistently outperforms others across all subregions, even within the same region, when compared to both MSWEP and CHIRPS. These results may be helpful when using NEX-GDDP-CMIP6 models for future projections and impact assessment studies in sub-Saharan Africa.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112316","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":"Estimating Extreme Drought Risk Through Classical and Bayesian Paradigms","authors":"Touqeer Ahmad,&nbsp;Safoorah Sabir,&nbsp;Irshad Ahmad Arshad,&nbsp;Taha Hasan,&nbsp;Olayan Albalawi","doi":"10.1002/joc.8705","DOIUrl":"https://doi.org/10.1002/joc.8705","url":null,"abstract":"<p>Drought poses significant challenges to both the environment and the economy, necessitating proactive mitigation strategies. This study introduces both classical and Bayesian Markov Chain Monte Carlo (MCMC) extreme value probabilistic models for quantifying drought risk. The models utilise the generalised extreme value (GEV) distribution to characterise the distribution of standardised precipitation index (SPI) and non-stationary standardised precipitation index (NSSPI) variables. Drought risk is probabilistically assessed across five regions in Baluchistan (a drought-prone area of Pakistan) over two 20-year periods per region. The study presents a novel approach in probabilistic quantification models, demonstrating slight performance improvement with the Bayesian MCMC paradigm, as evaluated by the continuously ranked probability scoring. Moreover, the application of the presented methodology can be extended to other climatic zones using Bayesian MCMC with informative priors constructed from historical records of the neighbouring regions.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8705","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112029","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":"Long-Term Changes in the Relative Humidity in Poland in 1966–2020","authors":"Ewelina Krawczyk","doi":"10.1002/joc.8706","DOIUrl":"https://doi.org/10.1002/joc.8706","url":null,"abstract":"<div>\u0000 \u0000 <p>The main purpose of this paper was to identify significant changes in air moisture conditions in Poland, which accompany climate warming. Meteorological data used in the research included the relative humidity (RH) values from 48 stations obtained from the Institute of Meteorology and Water Management—National Research Institute from 1966 to 2020. The monthly mean, standard deviation (SD) and coefficient of variation of RH from 12 PM for all months (with particular reference to the middle months of seasons—January, April, July and October) were used. Additionally, the dry weather (RH &lt; 30%) frequency in the warm half of the year was observed. Long-term changes were found by comparing relative humidity values in three 15-year subperiods (1966–1980, 1986–2000 and 2006–2020) and the statistical significance was estimated using the Mann-Kendall test. The most considerable long-term changes were noticed in April and July, especially in the last 15-year subperiod. The statistical significance was higher, mostly in warmer months. The SD was also higher in April and July than in January and October. Hence the humidity conditions in the warmer half of the year fluctuated more and more widely. A significant decrease in the RH mean values and an increase in SDs in spring and summer impact the increasing frequency of dry weather. Relations between meteorological characteristics suggest the warming climate contributes to drying the near-surface atmosphere but also impacts intensive precipitation events or snow cover parameters. The decreasing trend of long-term relative humidity may negatively impact the environment, human health and well-being and cause serious economic losses.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112030","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":"Rainfall From Brazilian Flying Rivers: Evaluating the Effectiveness of Precipitation Gridded Databases","authors":"Arthur Amaral e Silva,&nbsp;Leonardo Campos de Assis,&nbsp;Vitor Juste dos Santos,&nbsp;Laura Coelho de Andrade,&nbsp;Juliana Ferreira Lorentz,&nbsp;Bruno Silva Henriques,&nbsp;Maria Lucia Calijuri,&nbsp;Italo Oliveira Ferreira","doi":"10.1002/joc.8707","DOIUrl":"https://doi.org/10.1002/joc.8707","url":null,"abstract":"<div>\u0000 \u0000 <p>The uneven global distribution of rainfall significantly impacts water resources and environmental sustainability, emphasising the need for reliable climate prediction models. Accurate predictions are vital for sectors such as food security, urban planning and disaster management. Data from ground stations, radars and satellites are essential, despite challenges like instrumental errors. Satellites, with their comprehensive sensors, are crucial for atmospheric observations, aiding in the prediction of large-scale climatic events. Climate models such as CHIRPS, GLDAS, TerraClimate, and PERSIANN use different approaches to analyse precipitation data, which is key to understanding its spatial and temporal variability. This study evaluated (rainfall data) from these four climate models over 20 years (within the Brazilian territory), focusing on the spatiotemporal behaviour of rainfall using statistical metrics such as <i>R</i>\u0000 ², RMSE, and MAPE. The findings showed that CHIRPS had the best performance (<i>R</i>\u0000 ² = 0.843; RMSE = 42.83; MAPE = 0.09%), excelling in both overall database and extreme event analyses. TerraClimate, initially the lowest-performing model (<i>R</i>\u0000 ² = 0.413; RMSE = 91.56; MAPE = 0.23%), improved significantly when combined with elevation through multiple linear regression (MLR), achieving <i>R</i>\u0000 ² of 0.718, RMSE of 31.14, and MAPE of 9.56%. This made TerraClimate a viable model for studying the Flying Rivers. The study highlights that model selection should align with the specific characteristics of the area under consideration, with CHIRPS being particularly suitable for the studied region. This research enhances the understanding of the effectiveness of these models in estimating rainfall compared to in situ measurements, which is crucial for various applications. The authors advocate for further studies to advance research on the Flying Rivers, their significance, and the impacts of climate change on them.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 2","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112317","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":"Early-Stage Extratropical Cyclones' Mechanisms Over South America: RCM Added Value and Future Changes in a Warmer Planet","authors":"Carolina B. Gramcianinov,&nbsp;Andressa A. Cardoso,&nbsp;Natália P. da Silva,&nbsp;Rosa Luna-Niño,&nbsp;Natalia Castillo,&nbsp;Tereza Cavazos,&nbsp;Rosmeri P. da Rocha","doi":"10.1002/joc.8683","DOIUrl":"https://doi.org/10.1002/joc.8683","url":null,"abstract":"<p>Regional climate models (RCMs) from the CORDEX enable further investigations of the regional aspects of climate change impacts in South America. Here, we assess the CORDEX-RCMs' present and future projections of extratropical cyclones, focusing on their frequency, early-stage synoptic features, and added value relative to the global climate models (GCMs). Cyclones were tracked using a common algorithm in the present (1985–2005) and future RCP8.5 scenarios (2080–2099). ERA5 reanalysis was used as reference data in the present climate. Both GCMs and RCMs can identify the three major cyclone hot spots in South America: Argentina (ARG), La Plata Basin (LPB), and the south-southeast Brazilian coast (SBR). RCMs improve GCMs' representation of the cyclogenesis frequency, adding value by decreasing the biases (~10%). Early-stage cyclone synoptic structure also indicates RCMs' improvement of the low-level fields by presenting mesoscale structures of warm/cold advection and moisture flux convergence/divergence in greater agreement with ERA5 (except for moisture flux divergence for LPB). RCMs and GCMs project a general decrease in cyclogenesis for the end of the century. For the cyclogenesis cores, GCMs' and RCMs' projections agree on the trend signals in SBR, LPB, and ARG in austral winter and disagree in ARG in austral summer. For LPB and SBR cyclogenesis, the RCMs and GCMs suggest a future increase in moisture flux convergence and warm advection at low levels, while a decrease in upper level divergence is projected. This indicates a reinforcement of cyclogenesis (negative sea-level pressure trend) in the future due to the low-level features and associated diabatic processes. For ARG, the future trends in the mean structure of cyclogenesis are relatively weak. Following other studies, cyclogenesis frequency may decrease; however, changes could occur in some important physical processes, such as low-level moisture flux convergence and warm advection, suggesting more intense events in the future.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8683","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111545","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}