Pub Date : 2025-01-07DOI: 10.1016/j.atmosres.2025.107916
José Francisco León-Cruz
Tornadoes represent a significant threat to society. In Mexico, these natural hazards are common, principally from the end of spring until autumn, with a mean of around 45 events yearly (2013−2022). Although there is no official tornado database in Mexico with a proper tornado classification, it is known that supercell and non-supercell tornadogenesis is possible in the country. In this context, the present investigation examines the environments under 298 confirmed and validated tornadoes formed in the Mexican territory. Such analysis was made using the proximity-sounding approach with the ERA5 reanalysis dataset. In addition, using the k-means clustering method, three Tornadic Environment Types were found, each with specific characteristics. The first type is the most common environment, documented throughout the year, particularly during summer and the beginning of autumn. Intermediate instability conditions, without wind shear, and high humidity near the surface characterize it. The second type is observed in high altitudes during the spring, with relatively dry conditions and low unstable environments. The previous examples may relate to non-supercell tornadogenesis in different geographical regions and seasons. In contrast, the third type can be associated with significant tornadoes, an environment rich in instability and wind shear, concentrated in the northern portions of Mexico during spring. The findings of this research provide insights into increasing understanding of tornadoes in Mexico. Furthermore, it can be helpful to generate improvements in tornado forecasting at the national level, offering a range of tornadic environment types under which these natural hazards can develop. The clustering method results offer an alternative option for the classification of tornadoes in countries with little capacity for the official classification of these phenomena.
{"title":"Tornadic environments in Mexico","authors":"José Francisco León-Cruz","doi":"10.1016/j.atmosres.2025.107916","DOIUrl":"https://doi.org/10.1016/j.atmosres.2025.107916","url":null,"abstract":"Tornadoes represent a significant threat to society. In Mexico, these natural hazards are common, principally from the end of spring until autumn, with a mean of around 45 events yearly (2013−2022). Although there is no official tornado database in Mexico with a proper tornado classification, it is known that supercell and non-supercell tornadogenesis is possible in the country. In this context, the present investigation examines the environments under 298 confirmed and validated tornadoes formed in the Mexican territory. Such analysis was made using the proximity-sounding approach with the ERA5 reanalysis dataset. In addition, using the k-means clustering method, three Tornadic Environment Types were found, each with specific characteristics. The first type is the most common environment, documented throughout the year, particularly during summer and the beginning of autumn. Intermediate instability conditions, without wind shear, and high humidity near the surface characterize it. The second type is observed in high altitudes during the spring, with relatively dry conditions and low unstable environments. The previous examples may relate to non-supercell tornadogenesis in different geographical regions and seasons. In contrast, the third type can be associated with significant tornadoes, an environment rich in instability and wind shear, concentrated in the northern portions of Mexico during spring. The findings of this research provide insights into increasing understanding of tornadoes in Mexico. Furthermore, it can be helpful to generate improvements in tornado forecasting at the national level, offering a range of tornadic environment types under which these natural hazards can develop. The clustering method results offer an alternative option for the classification of tornadoes in countries with little capacity for the official classification of these phenomena.","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"84 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-05DOI: 10.1016/j.atmosres.2025.107914
Xianghua Wu, Miaomiao Ren, Linyi Zhou, Yashao Li, Jinghua Chen, Wanting Li, Kai Yang, Weiwei Wang
Causal analysis of cloud microphysical variables constitutes an effective means for characterizing the microphysical attributes and causal mechanisms of precipitation clouds. Causal analysis methods primarily rely on Granger causality tests based on lagged variables and linear regression. However, most cloud physical precipitation processes are nonlinear. Herein, a novel hybrid approach involving information entropy, wavelet decomposition, and Liang–Kleeman information flow is introduced to enhance the dependability and effectiveness of causal analysis for the self-organizing process of precipitation clouds in this paper. Based on the Weather Research and Forecasting (WRF) model, a case study is conducted of the northward-moving process of Typhoon Maysak in 2020. Gridded data with 30-min intervals and a 6 km × 6 km resolution is extracted. Through empirical analysis, using the total cloud water content (TWC) and water vapor mixing ratio (QV) as the principal variable and atmospheric vertical velocity (OMG), precipitable water (PW) and outgoing longwave radiation (OLR) as covariates, the hybrid causal analysis methodology is assessed. TWC and QV are direct and potential influencing factors of precipitation, respectively. Results indicate that the probability distributions of TWC and QV are significantly different at different stages. In the typhoon stage, typical self-organizing characteristics of high mean and low information entropy values are presented; in the tropical storm stage, information entropies increase, TWC increases, and QV decreases, with self-organizing characteristics weakening; in the tropical depression stage, both the mean and information entropies of TWC and QV show a significant decrease. Wavelet coherence analysis indicates that IEOLR and IEPW can better explain IETWC, and IEPW and IEOMG can better explain IEQV. There is a significant causal relationship between IETWC and IEPW at different time scales. At larger periodic scales, IEQV has significant causal relationships with IEOMG, IEPW and IEOLR. Overall, this approach provides insights into the complex causal relationships of cloud microphysical variables in a precipitation cloud system, broadening our understanding of these complex phenomena.
{"title":"Exploring the interconnections between total cloud water content and water vapor mixing ratio with other cloud microphysical variables in northward-moving typhoon precipitation via information entropy: A hybrid causal analysis approach using wavelet coherence and Liang–Kleeman information flow","authors":"Xianghua Wu, Miaomiao Ren, Linyi Zhou, Yashao Li, Jinghua Chen, Wanting Li, Kai Yang, Weiwei Wang","doi":"10.1016/j.atmosres.2025.107914","DOIUrl":"https://doi.org/10.1016/j.atmosres.2025.107914","url":null,"abstract":"Causal analysis of cloud microphysical variables constitutes an effective means for characterizing the microphysical attributes and causal mechanisms of precipitation clouds. Causal analysis methods primarily rely on Granger causality tests based on lagged variables and linear regression. However, most cloud physical precipitation processes are nonlinear. Herein, a novel hybrid approach involving information entropy, wavelet decomposition, and Liang–Kleeman information flow is introduced to enhance the dependability and effectiveness of causal analysis for the self-organizing process of precipitation clouds in this paper. Based on the Weather Research and Forecasting (WRF) model, a case study is conducted of the northward-moving process of Typhoon Maysak in 2020. Gridded data with 30-min intervals and a 6 km × 6 km resolution is extracted. Through empirical analysis, using the total cloud water content (TWC) and water vapor mixing ratio (QV) as the principal variable and atmospheric vertical velocity (OMG), precipitable water (PW) and outgoing longwave radiation (OLR) as covariates, the hybrid causal analysis methodology is assessed. TWC and QV are direct and potential influencing factors of precipitation, respectively. Results indicate that the probability distributions of TWC and QV are significantly different at different stages. In the typhoon stage, typical self-organizing characteristics of high mean and low information entropy values are presented; in the tropical storm stage, information entropies increase, TWC increases, and QV decreases, with self-organizing characteristics weakening; in the tropical depression stage, both the mean and information entropies of TWC and QV show a significant decrease. Wavelet coherence analysis indicates that IEOLR and IEPW can better explain IETWC, and IEPW and IEOMG can better explain IEQV. There is a significant causal relationship between IETWC and IEPW at different time scales. At larger periodic scales, IEQV has significant causal relationships with IEOMG, IEPW and IEOLR. Overall, this approach provides insights into the complex causal relationships of cloud microphysical variables in a precipitation cloud system, broadening our understanding of these complex phenomena.","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"131 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-05DOI: 10.1016/j.atmosres.2025.107913
Ji Yang, Mingjian Zeng, Long Wen, Kangyuan Sun, Yuanyuan Zheng, Wenru Shi
The occurrence of disaster-producing hourly extreme precipitation events (HEPEs) is usually linked to certain atmospheric backgrounds. Using high-density automatic weather stations observations and ERA5 reanalysis, this study analyzed the synoptic patterns of HEPEs over the Yangtze-Huaihe River Basin with an objective classification method. Four primary atmospheric circulation patterns (accounted for over 71 % of HEPEs) are identified, including two mei-yu types differ in different temporal and spatial features, the deep trough type, and the post-mei-yu type. The two mei-yu types are responsible for nearly 50 % of all HEPEs with relatively large horizontal size, and the southwesterly low-level jets that influenced by the cyclone and Western North Pacific Subtropical High (WNPSH), are a representative feature of these two types during HEPEs. The deep trough type during HEPEs related to Northeast China Cold Vortex is characterized by a cold northerly flow collided with the warm southerly/southwesterly flows, resulting in a strong convergence. In contrast, the HEPEs in the post-mei-yu type exhibits an eastward WNPSH, with the convergence and updrafts over the study area are caused by the collision between the southerly cyclone flows and the northerly flows at low levels. During two mei-yu types and post-mei-yu type, the HEPEs (non-precipitation) showed a cyclone (an anticyclone) feature. Our findings demonstrate the significant impact of circulation types on HEPEs, highlighting the importance of understanding their characteristics and patterns, which would be helpful for disaster warning, forecasting, and management.
{"title":"Synoptic patterns of hourly extreme precipitation events over the Yangtze-Huaihe River Basin in China","authors":"Ji Yang, Mingjian Zeng, Long Wen, Kangyuan Sun, Yuanyuan Zheng, Wenru Shi","doi":"10.1016/j.atmosres.2025.107913","DOIUrl":"https://doi.org/10.1016/j.atmosres.2025.107913","url":null,"abstract":"The occurrence of disaster-producing hourly extreme precipitation events (HEPEs) is usually linked to certain atmospheric backgrounds. Using high-density automatic weather stations observations and ERA5 reanalysis, this study analyzed the synoptic patterns of HEPEs over the Yangtze-Huaihe River Basin with an objective classification method. Four primary atmospheric circulation patterns (accounted for over 71 % of HEPEs) are identified, including two mei-yu types differ in different temporal and spatial features, the deep trough type, and the post-mei-yu type. The two mei-yu types are responsible for nearly 50 % of all HEPEs with relatively large horizontal size, and the southwesterly low-level jets that influenced by the cyclone and Western North Pacific Subtropical High (WNPSH), are a representative feature of these two types during HEPEs. The deep trough type during HEPEs related to Northeast China Cold Vortex is characterized by a cold northerly flow collided with the warm southerly/southwesterly flows, resulting in a strong convergence. In contrast, the HEPEs in the post-mei-yu type exhibits an eastward WNPSH, with the convergence and updrafts over the study area are caused by the collision between the southerly cyclone flows and the northerly flows at low levels. During two mei-yu types and post-mei-yu type, the HEPEs (non-precipitation) showed a cyclone (an anticyclone) feature. Our findings demonstrate the significant impact of circulation types on HEPEs, highlighting the importance of understanding their characteristics and patterns, which would be helpful for disaster warning, forecasting, and management.","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"83 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-03DOI: 10.1016/j.atmosres.2025.107910
Sreyasi Biswas, Charu Singh, Vidhi Bharti
The latest Global Precipitation Mission (GPM) IMERG V07B Final Run (Hereafter IMERG) has been validated for rainfall estimates in the North West Himalayan (NWH) region during the Indian Summer Monsoon (ISM) season (June–September) of 2000–2022. The validation is assessed against daily 0.25o x 0.25o India Meteorological Department (IMD) gridded rainfall data. We found that IMERG inherently underestimates rainfall, particularly low-intensity (< 50 mm day−1) rainfall. However, an overestimation is evident in high-intensity rainfall (50 mm day−1–200 mm day−1). This is consistent across all elevation ranges, from <1000 m to >5000 m, with the most significant negative bias observed at lower elevations. The proportion of such underestimated rainfall events increases with elevation, while the proportion of overestimated rainfall events decreases. Conclusively, IMERG is negatively skewed (−0.94). The proportion of accurate estimation of rainfall intensity is low and lies between 3 mm day−1 to 21 mm day−1 for <1000 m. IMERG performs the best in classifying a ‘rain event’ in Uttarakhand (UK) and Himachal Pradesh (HP), which is evident from near-optimal values of categorical metrics like False Alarm Ratio (FAR) (0.19 and 0.30 respectively), Probability of Detection (POD) (0.86 and 0.86 respectively), and Critical Success Index (CSI) (0.71 and 0.62 respectively). The classification of a “no rain event” by IMERG exhibits relatively low accuracy in the two states (Probability of False Detection (POFD) = 0.54 and 0.65 respectively). Overall, the Accuracy (ACC) in classifying a ‘rainfall event’, irrespective of it being a ‘rain event’ or a ‘no rain event’, is fairly good in UK (ACC = 0.75) and HP (ACC = 0.67) including the estimation of ‘rain event’ (Frequency Bias Index FBI = 1.07 and 1.23 respectively). The manifestation of stratiform rainfall in UK and HP could account for the underestimation of rainfall intensity and the discrepancies in the categorical metrics, owing to them being unrecognized by satellite due to warm cloud top temperatures. IMERG estimates are moderate over Jammu and Kashmir (JK) (FAR = 0.40, ACC = 0.1, CSI = 0.53, POFD = 0.64), while a large uncertainty in the performance of IMERG exists over Ladakh (LD) due to the paucity of IMD rain gauges (FAR = 0.62, ACC = 0.49, CSI = 0.34, POFD = 0.65).
{"title":"An assessment of GPM IMERG Version 7 rainfall estimates over the North West Himalayan region","authors":"Sreyasi Biswas, Charu Singh, Vidhi Bharti","doi":"10.1016/j.atmosres.2025.107910","DOIUrl":"https://doi.org/10.1016/j.atmosres.2025.107910","url":null,"abstract":"The latest Global Precipitation Mission (GPM) IMERG V07B Final Run (Hereafter IMERG) has been validated for rainfall estimates in the North West Himalayan (NWH) region during the Indian Summer Monsoon (ISM) season (June–September) of 2000–2022. The validation is assessed against daily 0.25<ce:sup loc=\"post\">o</ce:sup> x 0.25<ce:sup loc=\"post\">o</ce:sup> India Meteorological Department (IMD) gridded rainfall data. We found that IMERG inherently underestimates rainfall, particularly low-intensity (< 50 mm day<ce:sup loc=\"post\">−1</ce:sup>) rainfall. However, an overestimation is evident in high-intensity rainfall (50 mm day<ce:sup loc=\"post\">−1</ce:sup>–200 mm day<ce:sup loc=\"post\">−1</ce:sup>). This is consistent across all elevation ranges, from <1000 m to >5000 m, with the most significant negative bias observed at lower elevations. The proportion of such underestimated rainfall events increases with elevation, while the proportion of overestimated rainfall events decreases. Conclusively, IMERG is negatively skewed (−0.94). The proportion of accurate estimation of rainfall intensity is low and lies between 3 mm day<ce:sup loc=\"post\">−1</ce:sup> to 21 mm day<ce:sup loc=\"post\">−1</ce:sup> for <1000 m. IMERG performs the best in classifying a ‘rain event’ in Uttarakhand (UK) and Himachal Pradesh (HP), which is evident from near-optimal values of categorical metrics like False Alarm Ratio (FAR) (0.19 and 0.30 respectively), Probability of Detection (POD) (0.86 and 0.86 respectively), and Critical Success Index (CSI) (0.71 and 0.62 respectively). The classification of a “no rain event” by IMERG exhibits relatively low accuracy in the two states (Probability of False Detection (POFD) = 0.54 and 0.65 respectively). Overall, the Accuracy (ACC) in classifying a ‘rainfall event’, irrespective of it being a ‘rain event’ or a ‘no rain event’, is fairly good in UK (ACC = 0.75) and HP (ACC = 0.67) including the estimation of ‘rain event’ (Frequency Bias Index FBI = 1.07 and 1.23 respectively). The manifestation of stratiform rainfall in UK and HP could account for the underestimation of rainfall intensity and the discrepancies in the categorical metrics, owing to them being unrecognized by satellite due to warm cloud top temperatures. IMERG estimates are moderate over Jammu and Kashmir (JK) (FAR = 0.40, ACC = 0.1, CSI = 0.53, POFD = 0.64), while a large uncertainty in the performance of IMERG exists over Ladakh (LD) due to the paucity of IMD rain gauges (FAR = 0.62, ACC = 0.49, CSI = 0.34, POFD = 0.65).","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"3 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-03DOI: 10.1016/j.atmosres.2025.107911
Sougol Aghdasi, Peter J. Rayner, Nicholas M. Deutscher, Jeremy D. Silver
The paper investigates to what extent the assimilation of in-situ data over Gippsland, Victoria, Australia reduces uncertainties in methane emission sources on the regional scale. This was examined via a four-dimensional variational data assimilation system using the Community Multiscale Air Quality (CMAQ) transport-dispersion model. To evaluate the posterior error statistics of optimized monthly-mean methane emissions in Gippsland, we carried out a range of observing system simulation experiments. We ran the assimilations based on four selected months in 2019, employing a horizontal grid resolution of 2 km. The observation data are obtained based on three continuous observation instruments in the Gippsland region. As expected, the largest uncertainty reductions occur near observing sites. Also, our findings indicate that using a high-resolution model and in-situ observations provides detailed information on point sources but offers limited insight into area sources. The overall uncertainty for regional fluxes remains largely unchanged. Therefore, in-situ data is crucial for understanding point sources due to its detailed and localized nature. Finally, uncertainty reduction is much larger when the full concentration dataset is used rather than just the daytime data. This suggests the importance of model improvement to allow use of nighttime data, at least under conditions where the transport model can be expected to simulate atmospheric mixing well.
{"title":"Exploring uncertainty reduction in high-resolution methane emissions in Gippsland through in-situ data: A Bayesian inverse modeling and variational assimilation method","authors":"Sougol Aghdasi, Peter J. Rayner, Nicholas M. Deutscher, Jeremy D. Silver","doi":"10.1016/j.atmosres.2025.107911","DOIUrl":"https://doi.org/10.1016/j.atmosres.2025.107911","url":null,"abstract":"The paper investigates to what extent the assimilation of in-situ data over Gippsland, Victoria, Australia reduces uncertainties in methane emission sources on the regional scale. This was examined via a four-dimensional variational data assimilation system using the Community Multiscale Air Quality (CMAQ) transport-dispersion model. To evaluate the posterior error statistics of optimized monthly-mean methane emissions in Gippsland, we carried out a range of observing system simulation experiments. We ran the assimilations based on four selected months in 2019, employing a horizontal grid resolution of 2 km. The observation data are obtained based on three continuous observation instruments in the Gippsland region. As expected, the largest uncertainty reductions occur near observing sites. Also, our findings indicate that using a high-resolution model and in-situ observations provides detailed information on point sources but offers limited insight into area sources. The overall uncertainty for regional fluxes remains largely unchanged. Therefore, in-situ data is crucial for understanding point sources due to its detailed and localized nature. Finally, uncertainty reduction is much larger when the full concentration dataset is used rather than just the daytime data. This suggests the importance of model improvement to allow use of nighttime data, at least under conditions where the transport model can be expected to simulate atmospheric mixing well.","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"33 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-03DOI: 10.1016/j.atmosres.2025.107909
Wencai Liu, Ning Shi, Huijun Wang
Based on the JRA55 monthly reanalysis datasets and simplified numerical experiments, this study identifies several key regions in which precipitation has an evident influence on the seasonal march of the western North Pacific Subtropical High (WNPSH) from spring to summer. In May, there is an evident positive feedback between the developed trough low and the increased precipitation mainly around the Bay of Bengal with the aid of the thermal supply from the underlying ocean. This positive feedback facilitates the breakdown of the SH and the formation of the WNPSH as an independent circulation system. In June, Meiyu precipitation occurs and in turn stimulates an anticyclonic anomaly in the northwestern Pacific, which contributes as much as approximately 77 % to the first northward advance of the WNPSH therein. The second northward advance of the WNPSH in July is closely associated with the increased precipitation around Indian subcontinent, as the latter can explain as much as approximately 50 % of the observed vorticity anomaly over East Asia. After August, the precipitation increment pattern is almost reversed with respect to that during the previous months. Accordingly, the WNPSH retreats southward and gradually merges with the Iran High, restoring to a zonally uniform distribution pattern.
{"title":"Evolution of the western North Pacific subtropical high and impact of Asian precipitation from spring to summer","authors":"Wencai Liu, Ning Shi, Huijun Wang","doi":"10.1016/j.atmosres.2025.107909","DOIUrl":"https://doi.org/10.1016/j.atmosres.2025.107909","url":null,"abstract":"Based on the JRA55 monthly reanalysis datasets and simplified numerical experiments, this study identifies several key regions in which precipitation has an evident influence on the seasonal march of the western North Pacific Subtropical High (WNPSH) from spring to summer. In May, there is an evident positive feedback between the developed trough low and the increased precipitation mainly around the Bay of Bengal with the aid of the thermal supply from the underlying ocean. This positive feedback facilitates the breakdown of the SH and the formation of the WNPSH as an independent circulation system. In June, Meiyu precipitation occurs and in turn stimulates an anticyclonic anomaly in the northwestern Pacific, which contributes as much as approximately 77 % to the first northward advance of the WNPSH therein. The second northward advance of the WNPSH in July is closely associated with the increased precipitation around Indian subcontinent, as the latter can explain as much as approximately 50 % of the observed vorticity anomaly over East Asia. After August, the precipitation increment pattern is almost reversed with respect to that during the previous months. Accordingly, the WNPSH retreats southward and gradually merges with the Iran High, restoring to a zonally uniform distribution pattern.","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"84 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-03DOI: 10.1016/j.atmosres.2024.107906
Chenyi Yang, Yaoming Ma, Yuan Yuan, Hongchao Zuo
This study aims to comprehend the impact of surface states on precipitation and convection, with a focus on the Tibetan Plateau. The study examines the effects of energy distribution on the plateau and southern lowlands, comparing differences between the two regions through WRF simulations. The results reveal that changes in surface energy distribution can trigger both direct and indirect feedback on convective precipitation, and that the surface energy distribution controls how the total surface energy contributes to precipitation. This is reflected not only in effects on the spatial distribution, magnitude, and type of precipitation, but also on the timing and height of cloud formation. The study also examines the role of specific microphysical processes to the generation and dissipation of rainfall. The microphysical processes related to cold cloud rainfall are more significantly affected by surface energy distribution and exhibit negative feedback. The higher the proportion of cold cloud processes, the more significant the negative feedback. This coupling state characteristics are not limited by regions and can be generalized. Finally, this study investigated the boundary layer variables and microphysical variables in the entrainment layer and found that the existence of negative feedback in the dry coupling regime mainly depends on the stronger collision and aggregation effects brought about by the larger particles and stronger vertical motion.
{"title":"Surface energy distribution over the Tibetan Plateau and Southern Plain: Impact on convection development in dual coupling regime classification","authors":"Chenyi Yang, Yaoming Ma, Yuan Yuan, Hongchao Zuo","doi":"10.1016/j.atmosres.2024.107906","DOIUrl":"https://doi.org/10.1016/j.atmosres.2024.107906","url":null,"abstract":"This study aims to comprehend the impact of surface states on precipitation and convection, with a focus on the Tibetan Plateau. The study examines the effects of energy distribution on the plateau and southern lowlands, comparing differences between the two regions through WRF simulations. The results reveal that changes in surface energy distribution can trigger both direct and indirect feedback on convective precipitation, and that the surface energy distribution controls how the total surface energy contributes to precipitation. This is reflected not only in effects on the spatial distribution, magnitude, and type of precipitation, but also on the timing and height of cloud formation. The study also examines the role of specific microphysical processes to the generation and dissipation of rainfall. The microphysical processes related to cold cloud rainfall are more significantly affected by surface energy distribution and exhibit negative feedback. The higher the proportion of cold cloud processes, the more significant the negative feedback. This coupling state characteristics are not limited by regions and can be generalized. Finally, this study investigated the boundary layer variables and microphysical variables in the entrainment layer and found that the existence of negative feedback in the dry coupling regime mainly depends on the stronger collision and aggregation effects brought about by the larger particles and stronger vertical motion.","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"39 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-03DOI: 10.1016/j.atmosres.2025.107912
Josep Bonsoms, Juan I. López-Moreno, Marc Lemus-Cánovas, Marc Oliva
Snowfall is a crucial climate variable in mountainous regions: it influences hydrological and ecosystem dynamics and has a major impact on socioeconomic activities. This study examines the future changes (2024 to 2100) in winter (December, January and February, included) snowfall and extreme snow events in the Pyrenees, using a high-resolution dataset (2.5 km) derived from multiple CMIP5 General Circulation Models (GCMs) under RCP4.5 and RCP8.5 greenhouse gas scenarios, forced with the SAFRAN model. Winter snowfall shifts are examined considering accumulated snowfall (SF), extreme snowfall (Percentile >95th; SF95) per season, and return period levels (RPs) based on fitting Generalized Extreme Value to annually maximum SF. The data indicate an overall decline in SF across the entire mountain range and at all elevations. Trend analysis reveals a statistically significant negative evolution of SF (Tau Mann-Kendall >0.3; p-value ≤0.05) for most of the mountain range under RCP8.5. Projections for the end of the 21st century (2080–2100 period) anticipate reductions ranging from −9 % (RCP4.5; 2500–3000 m) to −29 % (RCP8.5; 1000–1500 m) compared to the historical climate (1960–2006 period). SF95 projections range from +2 % (RCP4.5; 2500–3000 m) to −25 % (RCP8.5; 2500–3000 m) for the same periods. Annual maximum extreme snowfall RPs indicate decreases over the historical period, regardless of the scenario and elevation range. These changes are attributed to warming and declining precipitation (P), with maximum P reductions reaching reduction of −24 % for RCP8.5 (2080–2100 period). Differences among GCMs contribute to a variability of ±20 % around the average multi-model mean. These results anticipate major terrestrial ecosystem changes in the Pyrenees, including significant spatiotemporal changes in hydrological resources potentially affecting millions of people living in large lowland cities.
{"title":"Future winter snowfall and extreme snow events in the Pyrenees","authors":"Josep Bonsoms, Juan I. López-Moreno, Marc Lemus-Cánovas, Marc Oliva","doi":"10.1016/j.atmosres.2025.107912","DOIUrl":"https://doi.org/10.1016/j.atmosres.2025.107912","url":null,"abstract":"Snowfall is a crucial climate variable in mountainous regions: it influences hydrological and ecosystem dynamics and has a major impact on socioeconomic activities. This study examines the future changes (2024 to 2100) in winter (December, January and February, included) snowfall and extreme snow events in the Pyrenees, using a high-resolution dataset (2.5 km) derived from multiple CMIP5 General Circulation Models (GCMs) under RCP4.5 and RCP8.5 greenhouse gas scenarios, forced with the SAFRAN model. Winter snowfall shifts are examined considering accumulated snowfall (SF), extreme snowfall (Percentile >95th; SF95) per season, and return period levels (RPs) based on fitting Generalized Extreme Value to annually maximum SF. The data indicate an overall decline in SF across the entire mountain range and at all elevations. Trend analysis reveals a statistically significant negative evolution of SF (Tau Mann-Kendall >0.3; <ce:italic>p</ce:italic>-value ≤0.05) for most of the mountain range under RCP8.5. Projections for the end of the 21st century (2080–2100 period) anticipate reductions ranging from −9 % (RCP4.5; 2500–3000 m) to −29 % (RCP8.5; 1000–1500 m) compared to the historical climate (1960–2006 period). SF95 projections range from +2 % (RCP4.5; 2500–3000 m) to −25 % (RCP8.5; 2500–3000 m) for the same periods. Annual maximum extreme snowfall RPs indicate decreases over the historical period, regardless of the scenario and elevation range. These changes are attributed to warming and declining precipitation (P), with maximum P reductions reaching reduction of −24 % for RCP8.5 (2080–2100 period). Differences among GCMs contribute to a variability of ±20 % around the average multi-model mean. These results anticipate major terrestrial ecosystem changes in the Pyrenees, including significant spatiotemporal changes in hydrological resources potentially affecting millions of people living in large lowland cities.","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"14 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-02DOI: 10.1016/j.atmosres.2024.107903
Karan Singh, Alok Sagar Gautam, N. Jeni Victor, Sanjeev Kumar, Swapnil S. Potdar, Kaupo Komsaare, Devendraa Siingh
In this study, the observation site Himalayan Cloud Observatory is located at the high-altitude location (30.34 N, 78.40 E, 1706 m above mean sea level) and established at Swami Ram Tirth Campus, Badshahithaul, Tehri Garhwal, Uttarakhand in the western Himalaya. We have identified and characterized the new particle formation events for 12-months period (January to December 2021) of continuous monitoring of the aerosol size distribution using NanoScan Scanning Mobility Particle Sizer. We have observed 51 new particle formation events out of 278 days of observations having 14 % frequency of new particle formation occurrence. New particle formation events were most frequent in March-April-May (pre-monsoon) and least frequent in June-July-August-September (monsoon). This trend is linked to high temperatures, strong solar radiation, and low relative humidity in pre-monsoon, which enhance the formation of low-volatility organic compounds, while in monsoon, wet scavenging reduces aerosol precursor gases. The seasonal mean of growth rate (GR<ce:inf loc="post">11.5-27.4 nm</ce:inf>), formation rate (J<ce:inf loc="post">11.5</ce:inf>), coagulation sink (CoagS<ce:inf loc="post">11.5-27.4</ce:inf>) and condensation sink (CS<ce:inf loc="post">TOT</ce:inf>, 11.5-154 nm) during the study period were 1.27 ± 0.23 nm h<ce:sup loc="post">-1</ce:sup>, 0.12 ± 0.08 cm<ce:sup loc="post">-3</ce:sup> s<ce:sup loc="post">-1</ce:sup>, 2.92 ± 1.65 × 10<ce:sup loc="post">-5</ce:sup> s<ce:sup loc="post">-1</ce:sup> and 9.91 ± 3.13 × 10<ce:sup loc="post">-3</ce:sup> s<ce:sup loc="post">-1</ce:sup> respectively. Seasonal distributions show particles within 11.5–100 nm predominantly originate from secondary emissions, while particles 100–154 nm result from both direct and nucleated process, highlighting the seasonal sources of particles at Himalayan Cloud Observatory. A significant reduction (by 25 %) found in incoming solar radiation on non-event days limits the oxidation of precursor gases, thereby inhibiting particle formation. Polar bivariate analysis reveals that winter airmasses, transported via mountain winds from the southwest and northeast, introduce mixed particle sizes. In contrast, the localized concentration of particles with elevated GR<ce:inf loc="post">11.5-27.4 nm</ce:inf> and J<ce:inf loc="post">11.5</ce:inf> during pre-monsoon highlights the role of aerosol precursors, condensable vapours, and favorable meteorological conditions, emphasizing new particle formation as the dominant particle source. Comparison with prior cloud condensation nuclei study at Himalayan Cloud Observatory reveals that new particle formation significantly supplements cloud condensation nuclei production beyond primary emissions, especially in pre-monsoon. The satellite-based observation of sulfur dioxide and formaldehyde complement and support the condensable vapours during event days at Himalayan Cloud Observatory. In summary, this research offers fresh perspectives on the characteriza
{"title":"Characteristics of new particle formation events at high-altitude location of Western Himalayan Region, Tehri Garhwal, India","authors":"Karan Singh, Alok Sagar Gautam, N. Jeni Victor, Sanjeev Kumar, Swapnil S. Potdar, Kaupo Komsaare, Devendraa Siingh","doi":"10.1016/j.atmosres.2024.107903","DOIUrl":"https://doi.org/10.1016/j.atmosres.2024.107903","url":null,"abstract":"In this study, the observation site Himalayan Cloud Observatory is located at the high-altitude location (30.34 N, 78.40 E, 1706 m above mean sea level) and established at Swami Ram Tirth Campus, Badshahithaul, Tehri Garhwal, Uttarakhand in the western Himalaya. We have identified and characterized the new particle formation events for 12-months period (January to December 2021) of continuous monitoring of the aerosol size distribution using NanoScan Scanning Mobility Particle Sizer. We have observed 51 new particle formation events out of 278 days of observations having 14 % frequency of new particle formation occurrence. New particle formation events were most frequent in March-April-May (pre-monsoon) and least frequent in June-July-August-September (monsoon). This trend is linked to high temperatures, strong solar radiation, and low relative humidity in pre-monsoon, which enhance the formation of low-volatility organic compounds, while in monsoon, wet scavenging reduces aerosol precursor gases. The seasonal mean of growth rate (GR<ce:inf loc=\"post\">11.5-27.4 nm</ce:inf>), formation rate (J<ce:inf loc=\"post\">11.5</ce:inf>), coagulation sink (CoagS<ce:inf loc=\"post\">11.5-27.4</ce:inf>) and condensation sink (CS<ce:inf loc=\"post\">TOT</ce:inf>, 11.5-154 nm) during the study period were 1.27 ± 0.23 nm h<ce:sup loc=\"post\">-1</ce:sup>, 0.12 ± 0.08 cm<ce:sup loc=\"post\">-3</ce:sup> s<ce:sup loc=\"post\">-1</ce:sup>, 2.92 ± 1.65 × 10<ce:sup loc=\"post\">-5</ce:sup> s<ce:sup loc=\"post\">-1</ce:sup> and 9.91 ± 3.13 × 10<ce:sup loc=\"post\">-3</ce:sup> s<ce:sup loc=\"post\">-1</ce:sup> respectively. Seasonal distributions show particles within 11.5–100 nm predominantly originate from secondary emissions, while particles 100–154 nm result from both direct and nucleated process, highlighting the seasonal sources of particles at Himalayan Cloud Observatory. A significant reduction (by 25 %) found in incoming solar radiation on non-event days limits the oxidation of precursor gases, thereby inhibiting particle formation. Polar bivariate analysis reveals that winter airmasses, transported via mountain winds from the southwest and northeast, introduce mixed particle sizes. In contrast, the localized concentration of particles with elevated GR<ce:inf loc=\"post\">11.5-27.4 nm</ce:inf> and J<ce:inf loc=\"post\">11.5</ce:inf> during pre-monsoon highlights the role of aerosol precursors, condensable vapours, and favorable meteorological conditions, emphasizing new particle formation as the dominant particle source. Comparison with prior cloud condensation nuclei study at Himalayan Cloud Observatory reveals that new particle formation significantly supplements cloud condensation nuclei production beyond primary emissions, especially in pre-monsoon. The satellite-based observation of sulfur dioxide and formaldehyde complement and support the condensable vapours during event days at Himalayan Cloud Observatory. In summary, this research offers fresh perspectives on the characteriza","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"20 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tropical cyclones (TCs) in the western North Pacific (WNP) can modulate the intensity of ENSO by weakening the Walker circulation and exciting or enhancing the eastward oceanic Kelvin waves. We find that WNP TCs have played an increasingly important role in the development of El Niño over the past 40 years, and that TCs contribute more to atmospheric circulation, SST and thermocline depth anomalies. The accumulated cyclone energy (ACE) in the WNP shows an enhanced explanatory capability for the Niño 3.4 index. TCs excite oceanic Kelvin waves with greater amplitudes compared to the past. Through diagnostic analysis of the temperature tendency equation, it is also found that TCs contribute more strongly to thermocline feedback and zonal advection feedback three months later. Consequently, it can be concluded that TCs play an increasingly significant positive feedback role in ENSO dynamics in the current climate context.
{"title":"Enhanced impact of western North Pacific tropical cyclones on El Niño intensity in the past 40 years","authors":"Xingfang Huang, Fei Huang, Hengxin Qu, Tingting Fan, Shibin Xu","doi":"10.1016/j.atmosres.2024.107907","DOIUrl":"https://doi.org/10.1016/j.atmosres.2024.107907","url":null,"abstract":"Tropical cyclones (TCs) in the western North Pacific (WNP) can modulate the intensity of ENSO by weakening the Walker circulation and exciting or enhancing the eastward oceanic Kelvin waves. We find that WNP TCs have played an increasingly important role in the development of El Niño over the past 40 years, and that TCs contribute more to atmospheric circulation, SST and thermocline depth anomalies. The accumulated cyclone energy (ACE) in the WNP shows an enhanced explanatory capability for the Niño 3.4 index. TCs excite oceanic Kelvin waves with greater amplitudes compared to the past. Through diagnostic analysis of the temperature tendency equation, it is also found that TCs contribute more strongly to thermocline feedback and zonal advection feedback three months later. Consequently, it can be concluded that TCs play an increasingly significant positive feedback role in ENSO dynamics in the current climate context.","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"131 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：