International Journal of Climatology最新文献

{"title":"Relative Contributions of Global Warming, ENSO and the Arctic Oscillation to Snow Cover and Their Projection on Surface Air Temperature and Snowfall in Sensitive Regions","authors":"Li Tao,&nbsp;Ye Jin,&nbsp;Chengyu Xu","doi":"10.1002/joc.8857","DOIUrl":"https://doi.org/10.1002/joc.8857","url":null,"abstract":"<div>\u0000 \u0000 <p>In this study, we explored the reasons for variability in monthly snow cover extent (SCE) in November–April during 1972–2021 in the Northern Hemisphere and clarified the relative contributions of global warming (GW), the El Niño–Southern Oscillation (ENSO), and the Arctic Oscillation (AO), as well as the relative contributions of local surface air temperature (SAT) and snowfall projected upon them. The study focused on regions where SCE showed a large standard deviation. Application of singular value decomposition and partial correlation methods showed that monthly SCE variability was affected predominantly by three modes: GW, ENSO and the AO. Based on multivariate information flow analysis, the impact of GW on SCE was found most pronounced on the Tibetan Plateau and in central Asia with a percentage contribution of &gt; 73% and &gt; 49%, respectively. The impact of the AO on SCE was found most pronounced in Europe, central-eastern North America, and the region east of Lake Baikal with a percentage contribution of &gt; 75%, &gt; 73% and &gt; 55%, respectively. The impact of ENSO on SCE was found most pronounced in western North America with a percentage contribution of &gt; 51%. The increased SCE related to GW in the eastern Tibetan Plateau can be attributed to southerly flows that transport moisture from the Indian Ocean and converge in the eastern Tibetan Plateau. Anomalous anticyclones related to positive phases of the AO and ENSO caused a reduction in snowfall and an increase in SAT, then a substantial decline in SCE.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 9","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144646946","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":"A Cold Frontal Life Cycle Climatology and Front–Cyclone Relationships Over the North Atlantic and Europe","authors":"Tobias Lichtenegger,&nbsp;Armin Schaffer,&nbsp;Albert Ossó,&nbsp;Oscar Martínez-Alvarado,&nbsp;Douglas Maraun","doi":"10.1002/joc.8830","DOIUrl":"https://doi.org/10.1002/joc.8830","url":null,"abstract":"<p>Atmospheric fronts and cyclones play an important role in day-to-day weather variability, especially in the mid-latitudes and during the winter season. Severe rainfall and windstorm events are often associated with the passage of a front or a cyclone. While there are many studies of individual fronts and climatologies of instantaneous fronts, there is no climatological study considering the whole frontal life cycle over time. Therefore, we use a front and cyclone tracking algorithm, together with a widely used front detection method, to detect and track cold fronts and cyclones over the North Atlantic and Europe in the extended winter season (October–March) in the ERA5 reanalysis data set. This enables a climatological study providing statistics of the frontal life cycle based on thousands of fronts. Several life cycle characteristics and frontal parameters are defined to investigate the frontal life cycle and the conditions and processes in the frontal region. Fronts are linked to their parent cyclone to study relationships between frontal and cyclonic properties. Cold fronts primarily develop over the Western North Atlantic and are found to decay at or soon after landfall on the European coast in most cases. Cold fronts tracked over the North Atlantic are found to last over 1 day longer and travel up to 1500 km farther on average than cold fronts tracked over the Mediterranean and over land. Cold frontal life cycle characteristics are strongly dependent on the North Atlantic Oscillation, with cold fronts appearing in a positive phase lasting longer and travelling faster and farther. Stronger cyclones are related to stronger frontal wind speeds at the surface as well as in the cold and warm sectors. The relationships between frontal and cyclonic properties are found to weaken over the course of their life cycle.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8830","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315053","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":"Precursors to Extreme Wintertime Cold in the Midwest United States","authors":"James M. Ryan,&nbsp;Ben Kravitz,&nbsp;Scott M. Robeson,&nbsp;Paul W. Staten","doi":"10.1002/joc.8849","DOIUrl":"https://doi.org/10.1002/joc.8849","url":null,"abstract":"<p>Cold air outbreaks (CAOs) are extreme weather events that affect millions of people every winter, including those in the US Midwest. Per our criteria (a sufficiently cold event over a wide area and a long period), we identified 43 wintertime CAOs in the Midwest region using data from 1980 to 2021 (approximately one per year). These occurred in the Midwest during three of five North American weather regimes. Two regimes' CAOs are related to a weak stratospheric polar vortex, consistent with previous research on CAOs in the neighbouring Great Plains region. A different regime, characterised by anomalous ridging along the west coast of North America, is the most common for Midwest CAOs, unlike in regions further to the west. Unlike the other two regimes, these so-called West Coast Ridge CAOs have no clear stratospheric connection. West Coast Ridge CAOs are instead linked to tropospheric processes on synoptic timescales, usually preceded by a weaker than average mid-tropospheric height gradient in the western Pacific about 10 days prior to CAO onset. Our results demonstrate a particular challenge for predicting some extreme events in the Midwest, with important implications for early warning systems.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8849","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144314968","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":"An Unexpected Outcome Followed an Apparent Seasonal Forecast of Opportunity and Prolonged Drought in Southwest Asia","authors":"Andrew Hoell,&nbsp;Melissa L. Breeden,&nbsp;Rochelle P. Worsnop,&nbsp;Rachel Robinson,&nbsp;Laurie Agel,&nbsp;Weston Anderson,&nbsp;Mathew Barlow,&nbsp;Harikishan Jayanthi,&nbsp;Amy McNally,&nbsp;Shradhannand Shukla,&nbsp;Kimberly Slinski,&nbsp;James Verdin,&nbsp;Fahim Zaheer","doi":"10.1002/joc.8851","DOIUrl":"https://doi.org/10.1002/joc.8851","url":null,"abstract":"<p>Despite forecasts to the contrary, Southwest Asia precipitation was unexpectedly below normal in October–December 2023, which extended an ongoing three-year drought that was responsible for water shortages and acute food insecurity. Expectations for above-normal precipitation in this season were based on predictions made the prior September from initialized forecast systems, which indicated a greater than 60% chance of such an occurrence. Confident above-normal precipitation predictions, making October–December 2023 an apparent forecast of opportunity, were due to attendant El Niño and positive Indian Ocean Dipole (PIOD) events. An ensemble of model simulations during 1991–2020 indicates that the simultaneous behaviour of these two phenomena is related to the tropical forcing of the mid-latitude circulation over Asia resembling a Gill–Matsuno response over India and China, which is associated with precipitation-enhancing low pressure over Southwest Asia. The co-action of these two modes is related to greater chances of above-normal Southwest Asia precipitation than if El Niño were acting alone. Southwest Asia precipitation in October–December 2023 was 13 mm below average (15 percentile) and was principally caused by two periods of protracted dryness that each lasted up to 3 weeks. During 26 November to 14 December, high pressure moved slowly eastward across western Asia at the same time as a strong MJO event moved across the Indian Ocean in its Phases 4 and 5, which are related to below-average Southwest Asia precipitation. Cumulative regional precipitation while the MJO was in Phases 4 and 5 during this period was −6 mm, accounting for 46% of the seasonal precipitation deficit in the region. During 26 October to 19 November, high pressure persisted with very little eastward movement over Southwest Asia while the MJO was weak, which suggests that the precipitation deficit during this time was caused by internal atmospheric variability in the extratropics.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8851","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315397","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":"Changes in Precipitation Patterns in Poland Derived From Projected Downscaled Future Climate Data From CMIP5 and CMIP6","authors":"Agnieszka Rutkowska,&nbsp;Patrick Willems,&nbsp;Santiago Mendoza Paz,&nbsp;Agnieszka Ziernicka-Wojtaszek","doi":"10.1002/joc.8822","DOIUrl":"https://doi.org/10.1002/joc.8822","url":null,"abstract":"<div>\u0000 \u0000 <p>Climate change is affecting the intensity and frequency of precipitation. The main objective was to assess future changes in precipitation patterns in Poland. Ensembles of daily precipitation projections for 70 stations from CMIP5 and CMIP6 under RCP(SSP)4.5, RCP(SSP)8.5 pathways were statistically downscaled using the Quantile Perturbation Method (QPM), covering the reference period 1961–1990 and future period 2071–2100. We assessed annual and seasonal (winter, summer) changes in 12 extreme Precipitation Indices (PIs), their distributions across Poland, and shifts in design annual maximum (AM) precipitation intensities. Statistical measures included distribution fitting, Intensity-Duration-Frequency curves, and return periods. The projected changes (CMIP6-8.5) in summer include: increase in the length of consecutive dry days (5%, on average), number of heavy precipitation days (4%) and 1-, 3-, 5-day maximum intensity (8%, 6%, 5%), and decrease in the number of wet days (6%) and length of consecutive wet days (6%). In winter, projections show an increase in the number of heavy precipitation days (30%), 1-,3-, 5-day maximum intensity (15%, 13%, 12%), and total precipitation (11%). The changes vary across Poland, with a more intense increase in the number of heavy precipitation days in the north-west (summer) and in the 1-day maximum intensity in the south (winter), higher precipitation totals in the south, southeast and coastal areas (winter), and a decrease in total precipitation in the south and east (summer). Uncertainty is large for the number of heavy precipitation days and maximum intensities, while it is low for total precipitation and the number of wet and dry days. Future return periods of extreme events are projected to shorten. A 100-year 1-day AM intensity can become a <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>49</mn>\u0000 <mo>−</mo>\u0000 <mn>66</mn>\u0000 </mrow>\u0000 </semantics></math>-year intensity. The results can be applied in flood and drought management plans, helping to adapt to future changes in precipitation patterns.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256488","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":"The Morphology of the Stratospheric Polar Vortex Under Stratospheric Aerosol Intervention Scenarios","authors":"Khalil Karami,&nbsp;Christoph Jacobi,&nbsp;Anish Kumar","doi":"10.1002/joc.8838","DOIUrl":"https://doi.org/10.1002/joc.8838","url":null,"abstract":"<p>Even though it is widely acknowledged that the stratospheric polar vortex (SPV) strengthens under stratospheric aerosol intervention (SAI), little is known about how the SPV's size, duration, location, and edge change under SAI compared to the present-day climate. Here, we address these issues using two large ensemble SAI simulations, namely GLENS (2060–2079) with extreme forcing and ARISE (2050–2069) with more moderate forcing. It is found that the wintertime Arctic and Antarctic stratospheric wind responses to SAI compared to the control (CTL) climate in GLENS (2060–2079) are roughly two times as large as in ARISE (2050–2069). While the zonal wind acceleration in ARISE (2050–2069) is hemispherically symmetric at 3–4 m s⁻¹ in the stratosphere of both hemispheres, the responses in GLENS (2060–2079) are hemispherically asymmetric, being two to three times larger in the Southern Hemisphere (SH, ~15 m s⁻¹) compared to the Northern Hemisphere (NH). While the edge of the vortex in GLENS (2060–2079) intensifies under SAI, similar changes are not found in ARISE (2050–2069). Such intensification of the vortex edge in GLENS is limited to lower stratosphere levels and does not extend to greater heights (~10 hPa). SAI has no discernible effect on the NH vortex morphology in ARISE simulations. However, the edge of the vortex intensifies in terms of Ertel's potential vorticity (EPV) gradient under SAI in the NH in GLENS. The greatest change that the SPV consistently shows under SAI in both GLENS and ARISE simulations is the SH spring vortex's behaviour. Under SAI, at 530 and 600 K, the vortex edge is weaker, its area is smaller, and it breaks up earlier than in the CTL runs.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8838","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315186","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":"ENSO Diversity Regulation of the Impact of MJO on Extreme Snowfall Events in the Peruvian Andes","authors":"Juan Sulca","doi":"10.1002/joc.8790","DOIUrl":"https://doi.org/10.1002/joc.8790","url":null,"abstract":"<p>Extreme snowfall events (ESEs) in the Peruvian Andes (10°–18.4° S, &gt; 4000 m) result in considerable economic losses. Despite their importance, how El Niño-Southern Oscillation (ENSO) diversity modulates the impact of the Madden–Julian Oscillation (MJO) on ESEs in the Peruvian Andes remains unexplored. Daily ERA5 reanalysis data from 1981 to 2018 were analysed. This study examines 16 ESEs. A bandpass filter with a 20–90-day range was applied to isolate the intraseasonal component of the daily anomalies. Additionally, time series data from the real-time multivariate MJO (RMM) index and Eastern and Central ENSO (E and C) indices were utilised. Composites were performed to describe the atmospheric circulation patterns related to ESEs in the Peruvian Andes under neutral, El Niño and La Niña conditions in the central and eastern Pacific Ocean. Under non-ENSO conditions, the MJO alone does not trigger ESEs in the Peruvian Andes during the DJF season. The absence of a well-organised convection system over the Peruvian Andes prevents ESEs. Conversely, during the JJA season, MJO Phases 5, 6 and 7 induce ESEs in the southern Peruvian Andes by enhancing moisture flux from the east through the equatorward propagation of an extratropical Rossby wave train that crosses South America and reaches the Altiplano region. In terms of ENSO diversity, the combined effects of the Central La Niña and MJO Phases 6 + 7 induce ESEs across the Western Cordillera of the southern Peruvian Andes during the DJF season. During austral winter, the interaction between the Central El Niño and MJO Phases 8 + 1, Eastern El Niño and MJO Phases 2 + 3, and Eastern La Niña and MJO Phases 8 + 1 induce ESEs across the Peruvian Andes.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8790","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256504","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":"Thunderstorm Forecasting by Using Machine Learning Techniques: A Comparative Model Analysis Leveraging Historic Climatic Records of Bangladesh","authors":"Mahiyat Tanzim,&nbsp;Sabina Yasmin","doi":"10.1002/joc.8853","DOIUrl":"https://doi.org/10.1002/joc.8853","url":null,"abstract":"<div>\u0000 \u0000 <p>Accurate thunderstorm forecasting is essential for protecting communities and minimising disruptions to agriculture, infrastructure and human lives, particularly in Bangladesh. However, predicting thunderstorms remains challenging due to the complex interplay of meteorological factors, data limitations and regional variations. This study addresses these challenges by integrating historical meteorological data with advanced machine learning and deep learning techniques to improve prediction accuracy. Using data from the Bangladesh Meteorological Department, we compare various models, evaluating their performance based on the coefficient of determination (<i>R</i>²) and root mean squared error (RMSE). Among traditional machine learning models, the Support Vector Machine (SVM) Regressor performed best with an <i>R</i>² of 0.658 and RMSE of 3.65. Among deep learning models, Convolutional Neural Networks (CNNs) achieved superior accuracy with an <i>R</i>² of 0.743 and RMSE of 3.17, effectively capturing spatial patterns in thunderstorm occurrences. Additionally, deep learning models such as CNN, ANN and LSTM successfully detected annual trends and fluctuations, improving prediction reliability. These findings highlight the potential of deep learning in enhancing thunderstorm forecasting, contributing to more effective disaster preparedness and risk management in thunderstorm-prone regions.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315216","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":"Contrasting Historical Trends in Equatorial Indian Ocean Zonal Sea Surface Temperature Gradient in CMIP6 Models","authors":"Mohan Soumya,&nbsp;Suresh Gopika","doi":"10.1002/joc.8832","DOIUrl":"https://doi.org/10.1002/joc.8832","url":null,"abstract":"<div>\u0000 \u0000 <p>The zonal sea surface temperature (SST) gradient in the tropical Indian Ocean (TIO) has been assessed using 50 climate models. Among these, 38 models exhibit an east–west negative gradient trend, indicating an intensified warming pattern in the Western Equatorial Indian Ocean (WEIO). This strong inter-model spread in representing the zonal SST gradient in the TIO mainly arises from the large variability of SST trends in the eastern Indian Ocean. The multi-model mean shows a westward SST gradient trend, which is approximately four-fold higher than the observed zonal gradient trend. However, models such as E3SM-1-1 and NESM3 realistically represent SST trends in both the eastern and western equatorial Indian Ocean regions, thereby capturing SST gradients close to observation. To investigate gradient variability and the underlying mechanisms, we categorised models into two groups, each comprising five models. The first group, comprising CESM2-FV2, EC-Earth3-Veg-LR, EC-Earth3-Veg, CAS-ESM2.0, and CIESM, demonstrates pronounced negative SST gradient trends. Conversely, the second group, consisting of CESM2-WACCM-FV2, CESM2, CESM2-WACCM, CMCC-CM2-SR5, and MIROC6, exhibits relatively subdued positive gradients, attributable to the slower warming of the WEIO. The inconsistent warming pattern formation, associated with eastward (westward) intensification of SST trends in positive (negative) gradient models, leads to larger gradient magnitudes compared to observations. The wind-evaporation-SST (WES) feedback plays a predominant role in shaping the SST warming pattern in both groups of models, while the mean state SST bias has a secondary role. The Bjerknes feedback is weak in positive zonal SST gradient models, whereas both Bjerknes and WES feedbacks act to enhance the zonal SST gradient in models with negative gradient trends. This study underscores the dominant role of air-sea interaction processes in forming SST warming patterns and highlights the unrealistic zonal SST gradient in the equatorial Indian Ocean.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315184","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":"Extreme Snow Decrement on the Tibetan Plateau in Early Spring of 2022","authors":"Chuying Deng,&nbsp;Xiuzhen Li,&nbsp;Yuan Zhao","doi":"10.1002/joc.8835","DOIUrl":"https://doi.org/10.1002/joc.8835","url":null,"abstract":"<div>\u0000 \u0000 <p>In early spring (March–April) of 2022, the snow depth on the Tibetan Plateau (TP) witnessed a historic decrement, breaking its records in the past few decades. The snow decrement was marked by an early beginning, a rapid pace of decline and extensive spatial coverage, which may play an important role in triggering the extreme events in the upcoming summer. This study investigated the underlying causes of this extreme snow decrement from the perspectives of local air–land interaction and crucial atmospheric circulations modulation. The extreme snow decrement can be attributed to a combination of factors, including an initial surplus in snow depth, anomalously high solar radiation influx, reduced precipitation and warm surface air temperature. Amongst these, the latter two factors were the key contributors leading to weakened snowfall (lowest) and increased snowmelt. Analysis of large-scale atmospheric circulation reveals the influence of a barotropically abnormal anticyclone (strongest) over the TP. The peripheral flow of this anticyclone suppressed the moisture supply, and the associated sinking motion (second strongest) enhanced the adiabatic heating (second highest). Further investigation suggests that this peculiar anticyclone might be linked to a robust positive North Atlantic Oscillation (NAO) signal. In conjunction with other favourable forcing and atmospheric conditions, the NAO triggered a wave train that propagated to the TP and contributed to the formation of the exceptional anticyclone.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 8","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315426","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}