International Journal of Climatology最新文献

{"title":"Mei-yu Front Assessment in CMIP6 Earth System Models During the East Asian Summer Monsoon","authors":"Kelvin S. Ng,&nbsp;Gregor C. Leckebusch,&nbsp;Kevin I. Hodges,&nbsp;Yaocun Zhang","doi":"10.1002/joc.8810","DOIUrl":"https://doi.org/10.1002/joc.8810","url":null,"abstract":"<p>The East Asian Summer Monsoon (EASM) plays a pivotal role in redistributing water across East Asia, including contributing a considerable flood risk due to the potential for localized extreme precipitation. To gain insights into future EASM changes, it is crucial to explore the dynamics of a core driver of extreme precipitation during the EASM, the Mei-yu front (MYF). While prior studies have examined various aspects of EASM in climate models, the comprehensive assessment of the dynamically important, that is, MYF remains largely unexplored. In this study, we evaluate the Mei-yu front representation in 38 CMIP6 models from May to August using the ECMWF Reanalysis version 5 (ERA5) as reference. Our findings reveal that several CMIP6 models struggle to accurately reproduce the MYF climatology, with performance varying by month. By categorizing models based on the east–west bias of MYF position in May, we identify distinct monthly evolutions in these biases during the EASM season. Our study shows a significant association between the misrepresentation of the MYF climatology in CMIP6 models and the misrepresentation of the Western North Pacific High, particularly its western edge. Other potential sources of biases are based on the misrepresentation of other large-scale circulation patterns, such as the South Asian High, and are also investigated. Furthermore, the performance evaluation of different aspects of the EASM is compared to previous studies, and the transferability of those principle evaluation findings is discussed.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8810","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256299","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":"Characterising Sensor-Level Errors of Global Satellite Precipitation Estimates for Different Rainfall Events","authors":"Hanqing Chen,&nbsp;Zhenyu Yu,&nbsp;Yuxian Yin,&nbsp;Rensheng Huang,&nbsp;Cuijuan Pang,&nbsp;Ping Zhou,&nbsp;Hongfei Mao","doi":"10.1002/joc.8817","DOIUrl":"https://doi.org/10.1002/joc.8817","url":null,"abstract":"<div>\u0000 \u0000 <p>Revealing sensor-level errors of global satellite precipitation estimates for different rainfall events is vital for understanding the error sources and components of ultimate satellite precipitation products at various rainfall events and is beneficial for improving the availability of satellite precipitation products in intensity-based hydro-meteorological applications such as drought analysis, extreme precipitation, typhoon monitoring and so on. However, investigations into sensor-level errors for various rainfall events are still lacking. To address this research gap, this study investigated the sensor-level errors in the Global Satellite Mapping of Precipitation for Global Precipitation Measurement (GPM-GSMaP) for mainland China by separating the total rainfall into six rainfall events (i.e., light rainfall, moderate rainfall, heavy rainfall, rainstorm, heavy rainstorm and extraordinary storm). The results indicated that the multi-sensor precipitation merging approach effectively reduces individual sensor errors but also inevitably propagates the shortcomings of various sensors into merging precipitation estimates, making it not the best way in most rainfall events. The performance rankings of the sensors varied depending on the error metrics, rainfall events, topography categories and climate types. In measuring light rainfall, the Advanced Microwave Sounding Unit-A/Microwave Humidity Sounder (AMSU-A/MHS) and infrared sensors were the major error sources of satellite precipitation products in most areas. Additionally, the AMSU-A/MHS sensors showed large normalised root mean square errors (&gt; 3.5) and biases (&gt; 80%) in estimating light, moderate, and heavy rainfall events in coastal areas and were dominant contributors that resulted in high measurement uncertainty of ultimate satellite precipitation products in coastal areas. As a core GPM sensor, the GPM Microwave Imager (GMI) sensor showed the worst performance in capturing light, moderate and heavy rainfall events, demonstrating that its current retrieval algorithms failed to leverage the hardware advantage fully. Finally, our research results highlighted that inversion algorithms of the satellite sensors need to consider the impact of different rainfall events on the inversion results to improve the accuracy of the sensor inversion.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256401","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":"An Adaptive Neuro-Fuzzy Inference System (ANFIS) and a Wavelet-Integrated ANFIS (WANFIS) for Univariate Bias-Correction of GCM-Simulated Temperature","authors":"Avijit Paul,&nbsp;Monomoy Goswami","doi":"10.1002/joc.8816","DOIUrl":"https://doi.org/10.1002/joc.8816","url":null,"abstract":"<div>\u0000 \u0000 <p>Correcting systematic errors or biases of raw outputs of a global climate model (GCM) simulating a climatological variable is an important requirement for the reliable use of these outputs in climate change impact assessments. In this study, a machine learning algorithm, namely Adaptive Neuro-Fuzzy Inference System (ANFIS), was first used for univariate bias correction of GCM-simulated outputs of daily maximum, mean, and minimum temperatures by considering one of these variables at a time. The ANFIS was then integrated with a discrete wavelet transform (DWT) in devising a novel bias-correction technique, named WANFIS, wherein (i) high- and low-frequency components of a time series of a temperature variable were first produced by DWT of that time series up to a pre-determined level of resolution, (ii) subsequently, an ANFIS was separately applied to each of the high- and low-frequency components of raw GCM-simulated data for correcting bias in relation to the corresponding components of the concurrent reference data and (iii) the bias-corrected components were finally aggregated by using DWT again to reconstruct the bias-corrected time series of the selected temperature variable. The performances of ANFIS and WANFIS were compared with that of a traditional univariate technique, quantile delta mapping (QDM), for correcting bias. The techniques were applied to gridded outputs of GCM-simulated temperature variables over diverse physiographic and climatic regions across mainland India. The ERA5 reanalysis data sets produced by the European Centre for Medium-Range Weather Forecasting were used as reference data for investigating relative performances. The WANFIS emerged as being an efficient bias-correction technique that consistently outperformed the ANFIS and QDM techniques in simulating spatiotemporally averaged as well as spatially distributed temperature variables, whereas some inconsistencies in performance were noted in the case of ANFIS and QDM. The discernible spatial patterns in the variation of performance measures under distinct physiographic and climatic conditions were also relatively uniformised towards higher levels of performance on application of WANFIS.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144255827","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 Examination of an Improved Analogue Method for Gridded Temperature Variation Reconstruction","authors":"Xuezhen Zhang,&nbsp;Xiaoyue Yan,&nbsp;Maowei Wu,&nbsp;Jingyun Zheng","doi":"10.1002/joc.8755","DOIUrl":"https://doi.org/10.1002/joc.8755","url":null,"abstract":"<div>\u0000 \u0000 <p>The analogue method (AM) is an approach for climate field reconstruction through combining proxy data and modelling data. This study improved the quantitative method of analogue pattern through considering the spatial distribution non-uniformity of proxy data (i.e., <i>k</i>\u0000 _{\u0000 <i>p</i>\u0000} term) and temperature changes capturing ability of proxy data (<i>v</i>\u0000 _{\u0000 <i>p</i>\u0000} term). Meanwhile, this study carries out pseudo-proxy experiments on temperature variations in the eastern Central Asia-East Asia region from 1902 to 1992 to examine the feasibility of the improved AM. The reconstruction results derived from improved AM match well with the instrumental data in terms of the temporal–spatial characteristics of temperature variation, with a correlations coefficient (<i>r</i>) of 0.5 (<i>p</i> &lt; 0.05) for the mean annual temperature (MAT) series, which is higher than that from original AM. The accuracy of the reconstruction results derived from improved AM is primarily depending on the ability of proxy data to capture temperature variations, and is secondly depending on the quantity of available proxy data. In the case of 75 pseudo-proxy maintaining the exactly same distribution with available proxy data but prescribed explaining variances of 100%, 66%, and 33%, there are respectively correlations of <i>r</i> = 0.54, 0.51, and 0.44 (<i>p</i> &lt; 0.05) between reconstructed and instrumental MAT series. When dealing with real proxies, whose explaining variances range from 4% to 24%, the correlation decreases to <i>r</i> = 0.28 (<i>p</i> &lt; 0.05). For a prescribed explaining variance of 100%, corresponding to 75, 37, and 5 proxies, the correlations are <i>r</i> = 0.54, 0.50, and 0.35 (<i>p</i> &lt; 0.05) respectively. These findings demonstrate the potential value of improved AM on the gridded temperature variation reconstruction and highlight the importance of proxy data quality.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143749661","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":"Interpolation of Hourly Surface Air Temperature—Application of a Spatio-Temporal Statistical Model in Complex Terrain","authors":"Louis Frey,&nbsp;Christoph Frei","doi":"10.1002/joc.8796","DOIUrl":"https://doi.org/10.1002/joc.8796","url":null,"abstract":"<div>\u0000 \u0000 <p>At present, grid datasets of in situ climate observations are mostly constructed in daily time resolution. An extension to sub-daily resolution is desirable, particularly for surface air temperature, in order to represent diurnal variations. Here, we devise and investigate a method to produce hourly temperature grids in a region of complex topography (Switzerland). The method, a dynamic linear model (DLM), extends a model widely used in spatial climatology (kriging with external drift, KED), into a spatio-temporal statistical model, while preserving its flexibility to adapt to the specifics of a region. We configure the method with covariates for known mesoscale effects (inversions, cold-air pooling, valley- and lake effects), assuming quasi-harmonic evolutions in the related coefficients. The method is applied to a wintertime inversion episode and a summertime high-pressure episode, with data from 259 stations. We compare DLM to a sequentially applied KED and evaluate the predictions in cross-validation. The results demonstrate that DLM can accurately reproduce complex spatio-temporal variations, including the gradual build-up of an inversion and the distinct temperature patterns between day- and night-time. The mean absolute error ranges from 0.65°C in flat and hilly terrain (both episodes) to 1.6°C in mountain valleys in winter. DLM yields temporally more continuous effect coefficients than KED, which corroborates the expected advantage from spatio-temporal modelling. However, the prediction errors of DLM are not significantly smaller, except in experiments where the station data was artificially reduced. It seems that the spatio-temporal approach had little advantage over a spatial model in the data-rich conditions of our application. However, its advantage may be more prominent in conditions with fewer observations or with more covariates. DLM is a versatile method for developing sub-daily climate datasets and this study provides valuable insight on its adoption to the climatic conditions of a specific region.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144255989","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":"Climatology and Trends of Various Oceanic and Atmospheric Parameters in the Arabian Sea Over the Last 45 Years","authors":"A. Anusree,&nbsp;V. P. Akhil,&nbsp;V. Sanil Kumar","doi":"10.1002/joc.8818","DOIUrl":"https://doi.org/10.1002/joc.8818","url":null,"abstract":"<div>\u0000 \u0000 <p>This study investigates the timescale variability of key atmospheric and oceanic variables in the Arabian Sea (AS) using 45 years (1979–2023) of data. Analyzing sea surface temperature (SST), wind components, precipitation, significant wave height, and peak wave period, notable regional and seasonal variations are identified. The northern AS experiences the highest surface warming at a rate of 0.15°C per decade. The westerlies have strengthened in the southwestern AS, while the northern AS displays a weakening trend. Along the northwest coast of India, the northerlies have intensified, but along the southwest coast of India, they have weakened. Precipitation trends have significant increases only along the southwest and northwest coasts of India. The significant wave height has increased across much of the AS, with a pronounced rise observed near the Somali coast (about 0.2 cm per year), and the peak period in the eastern AS has decreased, indicating a decline in long-period swells from the south. Even though this basin is strongly influenced by seasonal signals, the interannual variations in wave height anomalies are particularly significant in the central AS. Seasonal analysis reveals that the wave height in the central AS has a decreasing trend in June and August, despite being the peak monsoon months. This decrease corresponds with a similar decreasing trend in SST and westerlies, as well as an increase in the peak wave period. The study further explores the influence of dominant climate modes, such as the Indian Ocean Dipole (IOD) and El Niño-Southern Oscillation (ENSO), on the AS climate. Even though the phase agreement between IOD and ENSO is relatively good (<i>r</i> = 0.67) during the study period, the years 1997 and 2023 have notable differences in the meridional wind patterns, which in turn influence the significant wave height. These findings emphasise the need for adaptive strategies to address the impacts of climate variability and long-term trends on the marine environment of the AS.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256127","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":"Assessing the Deadly Heat Waves Over South Asian Cities: An Insights From UTCI and WBGT Indices","authors":"Najeebullah Khan,&nbsp;Sajjad Ahmad,&nbsp;Shamsuddin Shahid","doi":"10.1002/joc.8806","DOIUrl":"https://doi.org/10.1002/joc.8806","url":null,"abstract":"<div>\u0000 \u0000 <p>This study analysed South Asia's most devastating heat waves over the past four decades using ERA5 hourly reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Two heat stress indices, the Universal Thermal Climate Index (UTCI) and Wet Bulb Globe Temperature (WBGT), were employed to evaluate the characteristics, meteorological variable behaviour and diurnal temperature range (DTR) across four selected cities. The findings revealed that while both indices effectively captured heat wave events, WBGT demonstrated superior performance, particularly in assessing nighttime heat stress, where UTCI often underestimated the severity. For instance, during the 1995 heat wave in Bareilly, daytime UTCI exceeded the extreme heat stress threshold of 46.0°C during the second event but dropped close to the lower limit of 26.0°C at night. In contrast, nighttime WBGT consistently remained above the lowest threshold of 25.6°C. In Karachi (2015), WBGT surpassed the extreme heat stress level of 32.2°C during the day and remained above 25.6°C at night for consecutive days. Inland heat waves were marked by air temperature spikes above 40°C and reduced wind speeds (below 2 m/s), while coastal cities like Visakhapatnam experienced prolonged nighttime UTCI above 26.0°C and daytime values fluctuating between 38.0°C and 46.0°C. DTR analysis further demonstrated UTCI fluctuations exceeding 20°C during inland events, while WBGT remained within a 6.6°C range, highlighting its stability and better representation of persistent heat stress. Further analysis of the results revealed that higher WBGT sensitivity to local meteorological variables like relative humidity and wind speed has made it particularly effective in regions with high humidity.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144255976","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 Event Attribution in the Mediterranean","authors":"Aglaé Jézéquel,&nbsp;Davide Faranda,&nbsp;Philippe Drobinski,&nbsp;Piero Lionello","doi":"10.1002/joc.8799","DOIUrl":"https://doi.org/10.1002/joc.8799","url":null,"abstract":"<p>The Mediterranean basin is a hot spot of climate change in simulated scenarios, where effects are already observable. Increases in some climate extremes (terrestrial and marine heatwaves, agricultural droughts, extreme precipitation in some areas, and fire weather) are already observed. These extremes are expected to further increase in the future, together with more frequent pluvial and coastal floods, a reduction in cyclone and medicanes frequency (but increase of their maximum intensity) and increasing meteorological droughts. This review paper addresses methodological advances in the science of extreme event attribution, that is, techniques to better understand how much anthropogenic climate change affected the intensity, frequency and physical processes leading to observed extreme weather events, with a focus on studies in the Mediterranean basin.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8799","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144255977","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":"The Tibetan Plateau Westerly Jet Stream During July–August and Its Linkage With Precipitation in the Tibetan Plateau","authors":"Yuhan Feng,&nbsp;Sulan Nan,&nbsp;Ge Liu,&nbsp;Jingpeng Liu,&nbsp;Ting Zhang,&nbsp;Yuwei Zhou","doi":"10.1002/joc.8811","DOIUrl":"https://doi.org/10.1002/joc.8811","url":null,"abstract":"<div>\u0000 \u0000 <p>Using gridded and station-observed precipitation datasets from the China National Meteorological Information Center, GPCC precipitation data, and ERA5 reanalysis data from 1980 to 2021, this paper identifies a westerly jet to the north of the Tibetan Plateau (TP) during July–August, which differs from the typical East Asian westerly jet and is named the TP jet (TPJ). The relationship between the meridional location of the TPJ and precipitation in the TP and the associated mechanism are investigated. The results show that the TP precipitation is closely related to the meridional location of the TPJ. When the TPJ is located farther north, more-than-normal precipitation occurs in the central-western TP, and less-than-normal precipitation occurs in the southern part of eastern TP, thereby constituting an east–west antiphase mode. This mode is reversed when the TPJ is located farther south. The four-quadrant conceptual model of the jet stream can explain the link between the location of the TPJ and the mode of TP precipitation. When the TPJ is farther north, an anomalous meridional-vertical circulation cell appears at the entrance of the TPJ, with the central-western TP located at the upward branch of this cell. The upward motion is conducive to the convergence of water vapour and the increase in total cloud cover and produces more-than-normal precipitation in the central-western TP. Meanwhile, an anomalous meridional-vertical circulation cell appears at the exit of the TPJ, which is opposite to that at the TPJ entrance. The downward branch of this anomalous cell governs the southern part of eastern TP, causing water vapour divergence and suppressing total cloud cover and precipitation. The results suggest that the TPJ should be considered a special system when exploring the cause of TP summer precipitation.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144255978","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":"Predictability of the Indian Ocean Dipole: A Neural Network Approach","authors":"Rashi Aggarwal,&nbsp;Manpreet Kaur,&nbsp;K. C. Tripathi","doi":"10.1002/joc.8792","DOIUrl":"https://doi.org/10.1002/joc.8792","url":null,"abstract":"<div>\u0000 \u0000 <p>In light of the importance of the formation of dipoles in the Indian Ocean (IO), it becomes pertinent to investigate whether or not such events are inherently predictable. The authors investigate if the formation of a dipole is the result of local weather events or that of the dynamics of the system that generates the sea surface temperature (SST) time series. In the present study, artificial neural network prediction errors in different temporal regions have been analysed to answer the question for the 1997 event. It is found that the phenomenon was a consequence of the state of the SST system as a whole together with the evolution laws. As El-Nino and intraseasonal oscillations (ISO) are believed to have forced the formation of the 1997 dipole, the prediction errors are also analysed to statistically investigate such possibility. It is concluded that the ISO may provide the stochastic forcing to the Indian Ocean dipole (IOD) which is in agreement with the observations made by dynamical modelling of the system. The model is further evaluated for categorical forecast skills to forecast the anomalous points. The analysis shows that the model is capable of forecasting the anomalous points in the SST time series and that the dipole formation is a result of the deterministic laws governing the IO SST time series.</p>\u0000 </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 7","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144255975","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}