Pub Date : 2024-10-19DOI: 10.1016/j.atmosres.2024.107732
Yuefei Zeng , Kobra Khosravian , Yuxuan Feng , Alberto de Lozar , Ulrich Blahak
Since 2017, the SINFONY (Seamless INtegrated FOrecastiNg sYstem) project has been under development at the Deutscher Wetterdienst (DWD). It is aimed to provide a seamless ensemble system for early predictions and warnings of severe weather events by combining the nowcasting based on extrapolating observed radar reflectivity and short-term forecasts initiated from the Rapid Update Cycle (RUC) of data assimilation for the convection-permitting ICON (ICOsahedral Nonhydtostatic) model. So far, the ICON-RUC setup has been extensively tested for convective summer cases. In this study, a series of sensitivity experiments have been conducted for the winter precipitation, including the choice of microphysics schemes and the Latent Heat Nudging (LHN). Results show that within data assimilation cycles the two-moment scheme outperforms the one-moment scheme, and the LHN has also positive impacts. For the 6-h reflectivity forecasts, the two-moment scheme is clearly better than the one-moment scheme and the added values by using the LHN persist almost 6 h. For the precipitation forecasts, the two-moment scheme also exhibits advantage for the light precipitation, however, for the moderate precipitation, the one-moment scheme prevails. Current results indicate that the two-moment has to be enhanced for the moderate precipitation in winter.
{"title":"Investigating radar data assimilation for winter cases using ICON-KENDA system","authors":"Yuefei Zeng , Kobra Khosravian , Yuxuan Feng , Alberto de Lozar , Ulrich Blahak","doi":"10.1016/j.atmosres.2024.107732","DOIUrl":"10.1016/j.atmosres.2024.107732","url":null,"abstract":"<div><div>Since 2017, the SINFONY (Seamless INtegrated FOrecastiNg sYstem) project has been under development at the Deutscher Wetterdienst (DWD). It is aimed to provide a seamless ensemble system for early predictions and warnings of severe weather events by combining the nowcasting based on extrapolating observed radar reflectivity and short-term forecasts initiated from the Rapid Update Cycle (RUC) of data assimilation for the convection-permitting ICON (ICOsahedral Nonhydtostatic) model. So far, the ICON-RUC setup has been extensively tested for convective summer cases. In this study, a series of sensitivity experiments have been conducted for the winter precipitation, including the choice of microphysics schemes and the Latent Heat Nudging (LHN). Results show that within data assimilation cycles the two-moment scheme outperforms the one-moment scheme, and the LHN has also positive impacts. For the 6-h reflectivity forecasts, the two-moment scheme is clearly better than the one-moment scheme and the added values by using the LHN persist almost 6 h. For the precipitation forecasts, the two-moment scheme also exhibits advantage for the light precipitation, however, for the moderate precipitation, the one-moment scheme prevails. Current results indicate that the two-moment has to be enhanced for the moderate precipitation in winter.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"312 ","pages":"Article 107732"},"PeriodicalIF":4.5,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532610","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 : 2024-10-17DOI: 10.1016/j.atmosres.2024.107730
Hui Wang , Yuqing Wang
<div><div>In this study, the role of diabatic heating/cooling in outer rainbands (ORBs) in the formation and evolution of the secondary eyewall of a numerically simulated tropical cyclone (TC) is investigated. This is done through a series of sensitivity experiments under idealized conditions using a high-resolution cloud-resolving atmospheric model. The results show that artificially increasing diabatic heating in rainbands enhances convective activities in ORBs and leads to an earlier secondary eyewall formation (SEF), and later the faster weakening and earlier dissipation of the primary eyewall. Reducing diabatic heating in ORBs weakens the rainbands and delays the SEF but prolongs the duration of the double eyewall structure if the SEF occurs. Reducing diabatic cooling in ORBs enhances convective activity in rainbands but has little effect on convection in the primary eyewall prior to the SEF. However, it results in a widened eyewall structure and a stronger TC after the eyewall replacement. Increasing diabatic cooling in ORBs largely suppresses convection in rainbands and prohibits the SEF. These results demonstrate that diabatic heating/cooling in ORBs plays important roles in the SEF and evolution. Since diabatic heating/cooling in rainbands is sensitive to the near-core environmental relative humidity, our results demonstrate the critical importance of large-scale environmental moist condition to the formation and evolution of secondary eyewall in TCs. In addition, it is also found that when the area-averaged diabatic heating rate in ORBs becomes similar in magnitude to that in the primary eyewall, the secondary eyewall forms.</div></div><div><h3>Plain language summary</h3><div>Previous studies have demonstrated the importance of diabatic heating/cooling in outer rainbands to the structure and intensity changes of tropical cyclones (TCs) with a single eyewall. It is unclear whether and how diabatic heating/cooling in outer rainbands may affect the formation and evolution of the secondary eyewall in TCs. These issues have been addressed based on a series of sensitivity experiments under idealized conditions using a high-resolution atmospheric model. Results show that diabatic heating in outer rainbands is favorable for the secondary eyewall formation (SEF). Increasing diabatic heating in outer eyewall can lead to faster weakening and thus earlier dissipation of the primary eyewall. Diabatic cooling in outer rainbands suppresses convection in outer rainbands and prohibits the SEF. Since diabatic heating/cooling in outer rainbands is sensitive to the near-core environmental relative humidity, our results demonstrate the importance of the large-scale environmental moist condition to the SEF of TCs. We also found that when the area-averaged diabatic heating rate in outer rainbands becomes similar in magnitude to that in the primary eyewall, the secondary eyewall would form, which can be considered as a measure of the SEF in TCs.</div></div><di
在本研究中，研究了外雨带（ORB）中的绝热加热/冷却在数值模拟的热带气旋（TC）次生眼球的形成和演变中的作用。这是通过使用高分辨率云解析大气模型在理想化条件下进行的一系列敏感性实验完成的。结果表明，人为增加雨带中的二重加热会增强 ORB 中的对流活动，并导致更早的二次眼墙形成（SEF），以及更快的主眼墙减弱和更早的消散。减少 ORB 中的二重加热会减弱雨带，推迟 SEF 的形成，但如果出现 SEF，则会延长双层眼墙结构的持续时间。减少 ORB 的二重冷却会增强雨带中的对流活动，但对 SEF 前主眼墙中的对流影响不大。然而，它会导致眼墙结构扩大，并在眼墙替换后形成更强的热气旋。增加ORB中的二重冷却在很大程度上抑制了雨带中的对流，并阻止了SEF。这些结果表明，ORB中的二重加热/冷却在SEF和演变过程中发挥了重要作用。由于雨带中的二重加热/冷却对近核心环境相对湿度很敏感，我们的结果证明了大尺度环境湿度条件对TC中二次眼球的形成和演变至关重要。此外，我们还发现，当外雨带的区域平均二重加热速率与主眼球的二重加热速率大小相似时，就会形成副眼球。目前还不清楚外雨带中的二重加热/冷却是否以及如何影响热带气旋中二次眼墙的形成和演变。我们利用高分辨率大气模型，在理想化条件下进行了一系列敏感性实验，从而解决了这些问题。结果表明，外雨带的二重加热有利于二次眼墙的形成（SEF）。增加外雨带的二重加热会导致主雨带更快减弱，从而更早消散。外雨带的二重冷却会抑制外雨带的对流，从而阻碍 SEF 的形成。由于外雨带的二重加热/冷却对近核心环境相对湿度很敏感，我们的结果证明了大尺度环境湿度条件对TC的SEF的重要性。我们还发现，当外雨带的区域平均二重加热率与主眼球的二重加热率大小相近时，副眼球就会形成，这可被视为 TC 中 SEF 的一个衡量指标。3.当外雨带的区域平均二重加热率与眼墙的二重加热率大小相近时，就会形成副眼墙。
{"title":"The role of diabatic heating/cooling in outer rainbands in the secondary eyewall formation and evolution in a numerically simulated tropical cyclone","authors":"Hui Wang , Yuqing Wang","doi":"10.1016/j.atmosres.2024.107730","DOIUrl":"10.1016/j.atmosres.2024.107730","url":null,"abstract":"<div><div>In this study, the role of diabatic heating/cooling in outer rainbands (ORBs) in the formation and evolution of the secondary eyewall of a numerically simulated tropical cyclone (TC) is investigated. This is done through a series of sensitivity experiments under idealized conditions using a high-resolution cloud-resolving atmospheric model. The results show that artificially increasing diabatic heating in rainbands enhances convective activities in ORBs and leads to an earlier secondary eyewall formation (SEF), and later the faster weakening and earlier dissipation of the primary eyewall. Reducing diabatic heating in ORBs weakens the rainbands and delays the SEF but prolongs the duration of the double eyewall structure if the SEF occurs. Reducing diabatic cooling in ORBs enhances convective activity in rainbands but has little effect on convection in the primary eyewall prior to the SEF. However, it results in a widened eyewall structure and a stronger TC after the eyewall replacement. Increasing diabatic cooling in ORBs largely suppresses convection in rainbands and prohibits the SEF. These results demonstrate that diabatic heating/cooling in ORBs plays important roles in the SEF and evolution. Since diabatic heating/cooling in rainbands is sensitive to the near-core environmental relative humidity, our results demonstrate the critical importance of large-scale environmental moist condition to the formation and evolution of secondary eyewall in TCs. In addition, it is also found that when the area-averaged diabatic heating rate in ORBs becomes similar in magnitude to that in the primary eyewall, the secondary eyewall forms.</div></div><div><h3>Plain language summary</h3><div>Previous studies have demonstrated the importance of diabatic heating/cooling in outer rainbands to the structure and intensity changes of tropical cyclones (TCs) with a single eyewall. It is unclear whether and how diabatic heating/cooling in outer rainbands may affect the formation and evolution of the secondary eyewall in TCs. These issues have been addressed based on a series of sensitivity experiments under idealized conditions using a high-resolution atmospheric model. Results show that diabatic heating in outer rainbands is favorable for the secondary eyewall formation (SEF). Increasing diabatic heating in outer eyewall can lead to faster weakening and thus earlier dissipation of the primary eyewall. Diabatic cooling in outer rainbands suppresses convection in outer rainbands and prohibits the SEF. Since diabatic heating/cooling in outer rainbands is sensitive to the near-core environmental relative humidity, our results demonstrate the importance of the large-scale environmental moist condition to the SEF of TCs. We also found that when the area-averaged diabatic heating rate in outer rainbands becomes similar in magnitude to that in the primary eyewall, the secondary eyewall would form, which can be considered as a measure of the SEF in TCs.</div></div><di","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"312 ","pages":"Article 107730"},"PeriodicalIF":4.5,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532608","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}
The present study quantifies the improvement achieved in lightning forecast skill of the NCMRWF regional ensemble prediction system (NEPS-R) compared to its deterministic counterpart (CNTL). The lightning forecasts over study regions of East and Northeast India (ENEI) and Peninsular India (PI) during the pre-monsoon season and Central-East and Northeast India (CENEI) during the monsoon season have been verified using lightning observations from the Indian Institute of Tropical Meteorology (IITM) Lightning Detection Network (LDN). The persisting systematic negative bias in deterministic and EPS-based forecasts of the ensemble mean (EnsMean) and ensemble maximum (EnsMax) indicate the lack of spread among the members, supported by the low values of ensemble spread over all the study regions. EnsMean has the lowest RMSE, with a decrease in error ranging from 0.8 % to 2.18 % compared to CNTL. Categorical skill scores indicate that the EPS-based forecasts (EnsMean and EnsMax) are more skillful than the deterministic forecast at all thresholds and lead times. Further, Fractions Skill Score (FSS) establishes the superiority of the ensemble forecasts over the deterministic forecasts, where for threshold >1, EnsMean is skillful at comparatively smaller neighborhood sizes (ENEI and PI ∼68 km; CENEI ∼36 km for day-1) than CNTL (ENEI-116 km; PI-196 km; CENEI-68 km). EnsMax at higher thresholds (>5 and >10) is skillful at lesser neighborhood sizes ranging from 116 to 276 km compared to CNTL (>401 km) for day-1. Hence, skillful re-scaled EPS forecasts based on FSS could provide better guidance for the forecasters. The Continuous Ranked Probability Score of EPS forecasts is lower by around 9 % than the Mean Absolute Error of CNTL forecasts, and the ROC of EPS shows better discrimination of events and non-events compared to CNTL. These highlight the merits of using an EPS over a deterministic system for forecasting a field of high spatial variability, like lightning, and thereby, the use of vast computational resources to run a convective scale EPS is justified.
{"title":"Ensemble versus deterministic lightning forecast performance at a convective scale over Indian region","authors":"S. Kiran Prasad, Kumarjit Saha, Gauri Shanker, Ashish Routray, Abhijit Sarkar, V.S. Prasad","doi":"10.1016/j.atmosres.2024.107727","DOIUrl":"10.1016/j.atmosres.2024.107727","url":null,"abstract":"<div><div>The present study quantifies the improvement achieved in lightning forecast skill of the NCMRWF regional ensemble prediction system (NEPS-R) compared to its deterministic counterpart (CNTL). The lightning forecasts over study regions of East and Northeast India (ENEI) and Peninsular India (PI) during the pre-monsoon season and Central-East and Northeast India (CENEI) during the monsoon season have been verified using lightning observations from the Indian Institute of Tropical Meteorology (IITM) Lightning Detection Network (LDN). The persisting systematic negative bias in deterministic and EPS-based forecasts of the ensemble mean (EnsMean) and ensemble maximum (EnsMax) indicate the lack of spread among the members, supported by the low values of ensemble spread over all the study regions. EnsMean has the lowest RMSE, with a decrease in error ranging from 0.8 % to 2.18 % compared to CNTL. Categorical skill scores indicate that the EPS-based forecasts (EnsMean and EnsMax) are more skillful than the deterministic forecast at all thresholds and lead times. Further, Fractions Skill Score (FSS) establishes the superiority of the ensemble forecasts over the deterministic forecasts, where for threshold >1, EnsMean is skillful at comparatively smaller neighborhood sizes (ENEI and PI ∼68 km; CENEI ∼36 km for day-1) than CNTL (ENEI-116 km; PI-196 km; CENEI-68 km). EnsMax at higher thresholds (>5 and >10) is skillful at lesser neighborhood sizes ranging from 116 to 276 km compared to CNTL (>401 km) for day-1. Hence, skillful re-scaled EPS forecasts based on FSS could provide better guidance for the forecasters. The Continuous Ranked Probability Score of EPS forecasts is lower by around 9 % than the Mean Absolute Error of CNTL forecasts, and the ROC of EPS shows better discrimination of events and non-events compared to CNTL. These highlight the merits of using an EPS over a deterministic system for forecasting a field of high spatial variability, like lightning, and thereby, the use of vast computational resources to run a convective scale EPS is justified.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"312 ","pages":"Article 107727"},"PeriodicalIF":4.5,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532609","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 : 2024-10-16DOI: 10.1016/j.atmosres.2024.107731
Athanasios N. Natsis, Alkiviadis Bais, Charikleia Meleti
In this study, we investigate the characteristics of global horizontal irradiance enhancement events induced by clouds over Thessaloniki for the period 1994–2023 using data recorded every one minute. We identified the cloud enhancement (CE) events by creating an appropriate cloud-free irradiance reference using a radiative transfer model and aerosol optical depth data from a collocated Cimel sun photometer and a Brewer spectrophotometer. We found a trend in CE events of , and a trend in the corresponding irradiation of . To our knowledge, such long-term changes in CE events have not been presented in the past. The peak of the CE events was observed during May and June. CE events with duration longer than 10 min are very rare (), with exceptions lasting over an hour and up to 140 min. Finally, we have detected enhancements above the total solar irradiance at the top of the atmosphere for the same solar zenith angle of up to , with the 75 % of the cases below . Most of these extreme events occur in spring – early summer, with a secondary peak in autumn.
{"title":"Analysis of cloud enhancement events in a 30-year record of global solar irradiance at Thessaloniki, Greece","authors":"Athanasios N. Natsis, Alkiviadis Bais, Charikleia Meleti","doi":"10.1016/j.atmosres.2024.107731","DOIUrl":"10.1016/j.atmosres.2024.107731","url":null,"abstract":"<div><div>In this study, we investigate the characteristics of global horizontal irradiance enhancement events induced by clouds over Thessaloniki for the period 1994–2023 using data recorded every one minute. We identified the cloud enhancement (CE) events by creating an appropriate cloud-free irradiance reference using a radiative transfer model and aerosol optical depth data from a collocated Cimel sun photometer and a Brewer spectrophotometer. We found a trend in CE events of <span><math><mo>+</mo><mn>112</mn><mo>±</mo><mn>35</mn><mspace></mspace><mtext>cases</mtext><mo>/</mo><mtext>year</mtext></math></span>, and a trend in the corresponding irradiation of <span><math><mo>+</mo><mn>329.9</mn><mo>±</mo><mn>112.0</mn><mspace></mspace><mi>kJ</mi><mo>/</mo><mtext>year</mtext></math></span>. To our knowledge, such long-term changes in CE events have not been presented in the past. The peak of the CE events was observed during May and June. CE events with duration longer than 10 min are very rare (<span><math><mo><</mo><mn>8</mn><mo>%</mo></math></span>), with exceptions lasting over an hour and up to 140 min. Finally, we have detected enhancements above the total solar irradiance at the top of the atmosphere for the same solar zenith angle of up to <span><math><mn>204</mn><mspace></mspace><mi>W</mi><mo>/</mo><msup><mi>m</mi><mn>2</mn></msup></math></span>, with the 75 % of the cases below <span><math><mn>40</mn><mspace></mspace><mi>W</mi><mo>/</mo><msup><mi>m</mi><mn>2</mn></msup></math></span>. Most of these extreme events occur in spring – early summer, with a secondary peak in autumn.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"312 ","pages":"Article 107731"},"PeriodicalIF":4.5,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532709","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 : 2024-10-15DOI: 10.1016/j.atmosres.2024.107720
Shiksha Bastola , Jaepil Cho , Jonghun Kam , Younghun Jung
Global climate models (GCMs) serve as essential tools for projecting future climate trends, but their coarse resolution limits localized impact assessments in sectors like hydrology, agriculture, and biodiversity. Observation data with a spatial resolution of a few kilometers are crucial for downscaling and bias-correcting GCMs at finer resolutions. However, Nepal's extreme topography and organizational challenges have led to uneven distribution of meteorological stations and inconsistent data quality. Moreover, CMIP6-based climate extremes projections for the entire country are currently unavailable. To tackle these challenges, we developed a comprehensive national database for Nepal, offering high-resolution historical and projected precipitation and temperature data analyzed through 25 climate extreme indices from the Expert Team on Climate Change Detection and Indices (ETCCDI). Initially, observation grid data were prepared at a daily timescale with a spatial resolution of 0.05° × 0.05° for baseline period (1981–2010) using the Asian Precipitation High-Resolved Observational Data Integration Toward Evaluation (APHRODITE), the fifth generation of the European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5), and available good quality observed climate data. This data was then utilized to downscale and bias-correct 18 CMIP6 GCMs for 2015–2100 under four SSPs (1–2.6, 2–4.5, 3–7.0, 5–8.5). Quantile mapping was employed for the bias correction of the CMIP6 GCMs. The performance of the multimodal ensemble (MME) indicated better Nash-Sutcliffe Efficiency (NSE), root mean square error ratio (RSR), and Percent Bias (PBIAS) of climate extreme indices for the historical period. A comparative analysis was conducted across Nepal's major geographic regions to account for spatial variability in regional climate systems. The finer-resolution dataset can be crucial to deepen our understanding of climate impacts, and climate change, and eventually informing the policy-making in Nepal. Moreover, the methodology can be effectively replicated in data-scarce developing nations to promote climate research and adaptation efforts.
{"title":"Assessing the influence of climate change on multiple climate indices in Nepal using CMIP6 global climate models","authors":"Shiksha Bastola , Jaepil Cho , Jonghun Kam , Younghun Jung","doi":"10.1016/j.atmosres.2024.107720","DOIUrl":"10.1016/j.atmosres.2024.107720","url":null,"abstract":"<div><div>Global climate models (GCMs) serve as essential tools for projecting future climate trends, but their coarse resolution limits localized impact assessments in sectors like hydrology, agriculture, and biodiversity. Observation data with a spatial resolution of a few kilometers are crucial for downscaling and bias-correcting GCMs at finer resolutions. However, Nepal's extreme topography and organizational challenges have led to uneven distribution of meteorological stations and inconsistent data quality. Moreover, CMIP6-based climate extremes projections for the entire country are currently unavailable. To tackle these challenges, we developed a comprehensive national database for Nepal, offering high-resolution historical and projected precipitation and temperature data analyzed through 25 climate extreme indices from the Expert Team on Climate Change Detection and Indices (ETCCDI). Initially, observation grid data were prepared at a daily timescale with a spatial resolution of 0.05° × 0.05° for baseline period (1981–2010) using the Asian Precipitation High-Resolved Observational Data Integration Toward Evaluation (APHRODITE), the fifth generation of the European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5), and available good quality observed climate data. This data was then utilized to downscale and bias-correct 18 CMIP6 GCMs for 2015–2100 under four SSPs (1–2.6, 2–4.5, 3–7.0, 5–8.5). Quantile mapping was employed for the bias correction of the CMIP6 GCMs. The performance of the multimodal ensemble (MME) indicated better Nash-Sutcliffe Efficiency (NSE), root mean square error ratio (RSR), and Percent Bias (PBIAS) of climate extreme indices for the historical period. A comparative analysis was conducted across Nepal's major geographic regions to account for spatial variability in regional climate systems. The finer-resolution dataset can be crucial to deepen our understanding of climate impacts, and climate change, and eventually informing the policy-making in Nepal. Moreover, the methodology can be effectively replicated in data-scarce developing nations to promote climate research and adaptation efforts.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"311 ","pages":"Article 107720"},"PeriodicalIF":4.5,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445386","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 : 2024-10-15DOI: 10.1016/j.atmosres.2024.107728
Bicheng Huang , Shankai Tang , Yineng Rong , Tao Su , Yongping Wu , Shaobo Qiao , Guolin Feng
Meiyu (plume rain) is a distinctive weather phenomenon during boreal early summer, known for its increased precipitation during El Niño decay years bridged through the northwest Pacific anticyclone (NWPAC). It has been widely acknowledged that super El Niño (SEN) events consistently correspond to more Meiyu. This study highlights the instability in the relationship between El Niño and Meiyu, particularly during normal El Niño (NEN) decay years, where the probability of more or less Meiyu is almost equal by statistical analysis. Using the Liang-Kleeman information flow (LIF), our findings confirm that warming in the Maritime Continent (MC) induced by SEN leads to tropical North Atlantic warming in boreal spring. This suppresses northwest Pacific convection via Kevin waves and forms the north-south dipole mode of the NWPAC (EOF2), corresponding to strong Meiyu. Moreover, it is found that subtropical North Pacific cooling induced by NEN leads to the tropical North Atlantic warming in boreal spring via Pacific North American (PNA) pattern, reinforcing the region-wide consistent mode of the NWPAC (EOF1) via Rossby waves and resulting in strong Meiyu. Conversely, warming in the tropical North Atlantic induced by NEN in boreal early summer leads to anticyclonic circulation over the east of Japan (EOF3) and weak Meiyu. The contributions of these three causal structures to the uncertainty of Meiyu are 31 %, 25.7 %, and 28.2 %, respectively. This study sheds new light on the understanding the significance of NEN for Meiyu, emphasizing the importance of its causal relationship with warming in the tropical North Atlantic.
梅雨（羽流雨）是北方初夏的一种独特天气现象，因其在厄尔尼诺衰减年通过西北太平洋反气旋（NWPAC）增加降水而闻名。人们普遍认为，超强厄尔尼诺（SEN）事件总是与更多的梅雨相对应。本研究强调了厄尔尼诺和梅雨之间关系的不稳定性，特别是在正常厄尔尼诺衰减年，通过统计分析，出现或多或少梅雨的概率几乎相等。利用梁-克莱曼信息流（LIF），我们的研究结果证实，厄尔尼诺现象引起的海洋大陆（MC）变暖导致北大西洋热带地区在北方春季变暖。这通过凯文波抑制了西北太平洋对流，并形成了西北太平洋气旋的南北偶极模式（EOF2），与强梅雨相对应。此外，研究还发现，由 NEN 引起的副热带北太平洋变冷通过北美太平洋模式导致热带北大西洋在北方春季变暖，通过 Rossby 波加强了 NWPAC 的全区域一致模式（EOF1），从而导致强梅雨。相反，北半球初夏的 NEN 引起热带北大西洋变暖，导致日本东部出现反气旋环流（EOF3）和弱梅雨。这三个因果结构对 "梅雨 "不确定性的贡献率分别为 31%、25.7% 和 28.2%。这项研究为理解 NEN 对 Meiyu 的意义提供了新的启示，强调了 NEN 与热带北大西洋变暖之间因果关系的重要性。
{"title":"Disparity in Meiyu precipitation in the middle-lower Yangtze River basin during El Niño decay years","authors":"Bicheng Huang , Shankai Tang , Yineng Rong , Tao Su , Yongping Wu , Shaobo Qiao , Guolin Feng","doi":"10.1016/j.atmosres.2024.107728","DOIUrl":"10.1016/j.atmosres.2024.107728","url":null,"abstract":"<div><div>Meiyu (plume rain) is a distinctive weather phenomenon during boreal early summer, known for its increased precipitation during El Niño decay years bridged through the northwest Pacific anticyclone (NWPAC). It has been widely acknowledged that super El Niño (SEN) events consistently correspond to more Meiyu. This study highlights the instability in the relationship between El Niño and Meiyu, particularly during normal El Niño (NEN) decay years, where the probability of more or less Meiyu is almost equal by statistical analysis. Using the Liang-Kleeman information flow (LIF), our findings confirm that warming in the Maritime Continent (MC) induced by SEN leads to tropical North Atlantic warming in boreal spring. This suppresses northwest Pacific convection via Kevin waves and forms the north-south dipole mode of the NWPAC (EOF2), corresponding to strong Meiyu. Moreover, it is found that subtropical North Pacific cooling induced by NEN leads to the tropical North Atlantic warming in boreal spring via Pacific North American (PNA) pattern, reinforcing the region-wide consistent mode of the NWPAC (EOF1) via Rossby waves and resulting in strong Meiyu. Conversely, warming in the tropical North Atlantic induced by NEN in boreal early summer leads to anticyclonic circulation over the east of Japan (EOF3) and weak Meiyu. The contributions of these three causal structures to the uncertainty of Meiyu are 31 %, 25.7 %, and 28.2 %, respectively. This study sheds new light on the understanding the significance of NEN for Meiyu, emphasizing the importance of its causal relationship with warming in the tropical North Atlantic.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"312 ","pages":"Article 107728"},"PeriodicalIF":4.5,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532710","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 : 2024-10-13DOI: 10.1016/j.atmosres.2024.107729
Li Zongjie , Liu Mengqing , Li Hao , Liu Fang , Li Zongxing , Feng Qi , Xu Bin , Liu Xiaoying
This study quantitatively analyzed the contribution rate of recycled moisture to precipitation in the basin based on the Craig-Gordon model and the three-end-member mixing model through selecting 456 precipitation sample data collected from six sampling points in the source region of the Yellow River from September 2019 to August 2021. The results showed that: the contribution rate of moisture recycling to precipitation during the growing season is 40 %, and the total contribution to local moisture recycling is equivalent to 41 mm of precipitation. The contribution rate of evaporation and transpiration has obvious seasonal variation characteristics, showing a trend of decreasing first and then increasing in the source region of the Yellow River. Spatially, the contribution rate of evaporation and transpiration showed an increasing trend from south to north. It is assumed that all the precipitation generated by moisture recycling produces runoff, and the water yield is about 51 × 108 m3, which is 25 % of the total annual average runoff. In addition, the proportion of local moisture recirculation is mainly related to altitude, topography, vegetation coverage, and meteorological factors. Moisture recirculation is one of the important sources of precipitation in the source region of the Yellow River.
本研究通过选取2019年9月至2021年8月黄河源区6个采样点采集的456个降水样资料，基于Craig-Gordon模型和三端成员混合模型，定量分析了流域内循环水汽对降水的贡献率。结果表明：生长季水汽循环对降水的贡献率为 40%，对当地水汽循环的总贡献相当于 41 mm 降水量。蒸发蒸腾贡献率具有明显的季节变化特征，在黄河源区呈先减后增的趋势。从空间上看，蒸发蒸腾贡献率由南向北呈上升趋势。假设墒情循环产生的降水全部产生径流，产水量约为 51 × 108 m3，占年均径流总量的 25%。此外，当地水汽再循环的比例主要与海拔、地形、植被覆盖率和气象因素有关。水汽再循环是黄河源区降水的重要来源之一。
{"title":"Quantitative analysis of the contribution of moisture recycling to precipitation in the cold region","authors":"Li Zongjie , Liu Mengqing , Li Hao , Liu Fang , Li Zongxing , Feng Qi , Xu Bin , Liu Xiaoying","doi":"10.1016/j.atmosres.2024.107729","DOIUrl":"10.1016/j.atmosres.2024.107729","url":null,"abstract":"<div><div>This study quantitatively analyzed the contribution rate of recycled moisture to precipitation in the basin based on the Craig-Gordon model and the three-end-member mixing model through selecting 456 precipitation sample data collected from six sampling points in the source region of the Yellow River from September 2019 to August 2021. The results showed that: the contribution rate of moisture recycling to precipitation during the growing season is 40 %, and the total contribution to local moisture recycling is equivalent to 41 mm of precipitation. The contribution rate of evaporation and transpiration has obvious seasonal variation characteristics, showing a trend of decreasing first and then increasing in the source region of the Yellow River. Spatially, the contribution rate of evaporation and transpiration showed an increasing trend from south to north. It is assumed that all the precipitation generated by moisture recycling produces runoff, and the water yield is about 51 × 10<sup>8</sup> m<sup>3</sup>, which is 25 % of the total annual average runoff. In addition, the proportion of local moisture recirculation is mainly related to altitude, topography, vegetation coverage, and meteorological factors. Moisture recirculation is one of the important sources of precipitation in the source region of the Yellow River.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"311 ","pages":"Article 107729"},"PeriodicalIF":4.5,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445384","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 : 2024-10-13DOI: 10.1016/j.atmosres.2024.107726
Jing Ren , Chunlin Huang , Jinliang Hou , Ying Zhang , Pengfei Ma , Ling Yang
In this study, the investigation is made to reveal the impact of multi-strategically assimilating Global Precipitation Measurement (GPM) precipitation and Himawari-8/Advanced Himawari Imager (AHI) water vapor radiances (WVR) on forecasting a heavy snowfall event in the Eastern Qinghai-Tibet Plateau (EQTP) employing the Weather Research and Forecast model (WRF) and the Four-Dimensional Variational (4DVar) assimilation system (WRF-4DVar). The multiple data assimilation (DA) strategies include control tests (CON), the individual assimilation of AHI and GPM tests (DA_AHI and DA_GPM) and the joint assimilation of GPM and AHI (DA_G&A), with different initial times. The results indicate that GPM precipitation effectively captures mesoscale atmospheric details, but its scope is confined to a limited area. AHI WVR is sensitive to upper-middle atmospheric humidity and furnishes extensive-scale environmental parameters such as water vapor transport characteristics. The joint assimilation of the two not only yields multi-dimensional atmospheric insights but also addresses the limitations of individual assimilation. Assimilation GPM and AHI are respective sensitivity to the lower layers (about 800hpa) and upper layers (about 400hpa) of model. The individual assimilation GPM has the greatest effect on near-surface humidity field, and AHI plays a dominant role in the joint assimilation. By assimilating different remote sensing products at different initial times of NWPs, the thermodynamic and dynamic structures are variously reconstructed, leading to the different snowfall scenes. In addition, we further compare the 12-hourly cumulative snowfall with in-situ meteorological station observations. The predictions of snowfall from DA_G&A perform much better with the correlation coefficient (CC) and root-mean-square error (RMSE) 0.36 and 3.14 mm, respectively. As for different initial times of NWPs, the best snowfall forecast is 0600 UTC on October 28, 2022, and the CC is 0.4. Nevertheless, accurately predicting precipitation areas, intensity, and temporal variations remains challenging, particularly for solid precipitation like snowfall. Thus, meticulous consideration of weather process characteristics, observation attributes, and relevant parameter configurations during DA are imperative to enhance the efficiency of observation data utilization.
{"title":"Impact of the combined assimilation of GPM/IMGER precipitation and Himawari-8/AHI water vapor radiance on snowfall forecasts using WRF model and 4Dvar system","authors":"Jing Ren , Chunlin Huang , Jinliang Hou , Ying Zhang , Pengfei Ma , Ling Yang","doi":"10.1016/j.atmosres.2024.107726","DOIUrl":"10.1016/j.atmosres.2024.107726","url":null,"abstract":"<div><div>In this study, the investigation is made to reveal the impact of multi-strategically assimilating Global Precipitation Measurement (GPM) precipitation and Himawari-8/Advanced Himawari Imager (AHI) water vapor radiances (WVR) on forecasting a heavy snowfall event in the Eastern Qinghai-Tibet Plateau (EQTP) employing the Weather Research and Forecast model (WRF) and the Four-Dimensional Variational (4DVar) assimilation system (WRF-4DVar). The multiple data assimilation (DA) strategies include control tests (CON), the individual assimilation of AHI and GPM tests (DA_AHI and DA_GPM) and the joint assimilation of GPM and AHI (DA_G&A), with different initial times. The results indicate that GPM precipitation effectively captures mesoscale atmospheric details, but its scope is confined to a limited area. AHI WVR is sensitive to upper-middle atmospheric humidity and furnishes extensive-scale environmental parameters such as water vapor transport characteristics. The joint assimilation of the two not only yields multi-dimensional atmospheric insights but also addresses the limitations of individual assimilation. Assimilation GPM and AHI are respective sensitivity to the lower layers (about 800hpa) and upper layers (about 400hpa) of model. The individual assimilation GPM has the greatest effect on near-surface humidity field, and AHI plays a dominant role in the joint assimilation. By assimilating different remote sensing products at different initial times of NWPs, the thermodynamic and dynamic structures are variously reconstructed, leading to the different snowfall scenes. In addition, we further compare the 12-hourly cumulative snowfall with in-situ meteorological station observations. The predictions of snowfall from DA_G&A perform much better with the correlation coefficient (CC) and root-mean-square error (RMSE) 0.36 and 3.14 mm, respectively. As for different initial times of NWPs, the best snowfall forecast is 0600 UTC on October 28, 2022, and the CC is 0.4. Nevertheless, accurately predicting precipitation areas, intensity, and temporal variations remains challenging, particularly for solid precipitation like snowfall. Thus, meticulous consideration of weather process characteristics, observation attributes, and relevant parameter configurations during DA are imperative to enhance the efficiency of observation data utilization.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"311 ","pages":"Article 107726"},"PeriodicalIF":4.5,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445387","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 : 2024-10-11DOI: 10.1016/j.atmosres.2024.107725
Waheed Ullah , Khameis Alabduoli , Safi Ullah , Sami G. Al-Ghamdi , Khawla Alhebsi , Mansour Almazroui , Mazen E. Assiri , Waqar Azeem , Abdelgadir Abuelgasim , Daniel Fiifi Tawia Hagan
The 2-m temperature data is a significant indicator for studying the weather extremes and the exchange of water and energy fluxes between the surface and atmosphere. This study compared three reanalysis datasets, i.e., ERA5, ERA5-Land, and MERRA-2, with observations from in-situ sources from 1990 to 2022 using various statistical error metrics and extreme temperature indices over the Arabian Peninsula (AP) region. We selected these reanalysis datasets due to the continuous improvements and higher spatiotemporal output better capturing the temperature variability. The spatiotemporal climatology shows lower temperatures in winter (<15 °C) and maximum in summer (>35 °C); however, the reanalysis data show more deviations in temperature during the cold season than in the warm season. The reanalysis data underestimated the frequency of the cold (<10 °C) and hot (>30 °C) days across the four regions, except ERA5-Land, which closely followed observed data. The strength of the correlation shows better performance (>0.90) in the cold extremes (cold nights and cold days) frequency than the hot extremes. On an interannual scale, reanalysis products exhibit strong correlations (>0.90) with in-situ data across most regions, particularly in winter and autumn, moderate in spring, and weaker in summer. The reanalysis data shows negative biases in the inland regions and positive biases in the coastal areas with consistent root mean square differences (RMSD) spatiotemporally. The differences in performance are due to the topography and poor representation of the energy fluxes, especially in MERRA-2 as well as missing data in observations. This study recommends ERA5-Land as the first choice for extreme weather simulations in the region, followed by MERRA-2 and ERA5 on the same scale, but proper attention is needed when using reanalysis data for cold and hot extremes.
{"title":"Comparison of 2-m surface temperature data between reanalysis and observations over the Arabian Peninsula","authors":"Waheed Ullah , Khameis Alabduoli , Safi Ullah , Sami G. Al-Ghamdi , Khawla Alhebsi , Mansour Almazroui , Mazen E. Assiri , Waqar Azeem , Abdelgadir Abuelgasim , Daniel Fiifi Tawia Hagan","doi":"10.1016/j.atmosres.2024.107725","DOIUrl":"10.1016/j.atmosres.2024.107725","url":null,"abstract":"<div><div>The 2-m temperature data is a significant indicator for studying the weather extremes and the exchange of water and energy fluxes between the surface and atmosphere. This study compared three reanalysis datasets, i.e., ERA5, ERA5-Land, and MERRA-2, with observations from in-situ sources from 1990 to 2022 using various statistical error metrics and extreme temperature indices over the Arabian Peninsula (AP) region. We selected these reanalysis datasets due to the continuous improvements and higher spatiotemporal output better capturing the temperature variability. The spatiotemporal climatology shows lower temperatures in winter (<15 °C) and maximum in summer (>35 °C); however, the reanalysis data show more deviations in temperature during the cold season than in the warm season. The reanalysis data underestimated the frequency of the cold (<10 °C) and hot (>30 °C) days across the four regions, except ERA5-Land, which closely followed observed data. The strength of the correlation shows better performance (>0.90) in the cold extremes (cold nights and cold days) frequency than the hot extremes. On an interannual scale, reanalysis products exhibit strong correlations (>0.90) with in-situ data across most regions, particularly in winter and autumn, moderate in spring, and weaker in summer. The reanalysis data shows negative biases in the inland regions and positive biases in the coastal areas with consistent root mean square differences (RMSD) spatiotemporally. The differences in performance are due to the topography and poor representation of the energy fluxes, especially in MERRA-2 as well as missing data in observations. This study recommends ERA5-Land as the first choice for extreme weather simulations in the region, followed by MERRA-2 and ERA5 on the same scale, but proper attention is needed when using reanalysis data for cold and hot extremes.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"311 ","pages":"Article 107725"},"PeriodicalIF":4.5,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-10DOI: 10.1016/j.atmosres.2024.107721
Jialing Xin , Yuanjie Zhang , Weihua Bai , Zhaokai Song
This study characterizes the variation of the urban heat island (UHI) within the planetary boundary layer (PBL) and investigates the horizontal advection effects on the UHI variation throughout a heat wave (HW) event over Shanghai municipality in August 2019 based on numerical model simulations. It is found that the UHI intensifies under HW conditions with the UHI intensity gradually weakening from the surface upwards. The daytime UHIs during the HW are 3.68 K (29.27 %), 1.41 K (33.52 %) and 1.04 K (36.97 %) higher than those during the pre-HW at the surface, near-surface and in the PBL, respectively, while the nighttime UHIs have no significant response to the HW at least for this case. The mean UHIs during the HW period at the surface, near-surface (2 m) and in the PBL are 6.83 K (2.68 K), 2.45 K (1.34 K), and 1.73 K (0.04 K) in the daytime (nighttime), respectively. The PBL UHI generally exists only in the daytime potentially caused by the thermal convective diffusion. The near-surface and PBL UHIs are significantly affected by the horizontal advection, resulting in different UHI intensities and variations against rural regions in different orientations. Cold advection from the Yangtze River (the ocean) in the riverside (coastal) rural region corresponds to the great UHI intensification, while the strong cold advection in the urban region well explains the fast UHI weakening. This study highlights that, besides local thermal factors, synoptic circulation also play an important role in the interaction between the UHI effect and HW events.
{"title":"Response of urban heat island effects within the planetary boundary layer to heat waves and impact of horizontal advection over Shanghai","authors":"Jialing Xin , Yuanjie Zhang , Weihua Bai , Zhaokai Song","doi":"10.1016/j.atmosres.2024.107721","DOIUrl":"10.1016/j.atmosres.2024.107721","url":null,"abstract":"<div><div>This study characterizes the variation of the urban heat island (UHI) within the planetary boundary layer (PBL) and investigates the horizontal advection effects on the UHI variation throughout a heat wave (HW) event over Shanghai municipality in August 2019 based on numerical model simulations. It is found that the UHI intensifies under HW conditions with the UHI intensity gradually weakening from the surface upwards. The daytime UHIs during the HW are 3.68 K (29.27 %), 1.41 K (33.52 %) and 1.04 K (36.97 %) higher than those during the pre-HW at the surface, near-surface and in the PBL, respectively, while the nighttime UHIs have no significant response to the HW at least for this case. The mean UHIs during the HW period at the surface, near-surface (2 m) and in the PBL are 6.83 K (2.68 K), 2.45 K (1.34 K), and 1.73 K (0.04 K) in the daytime (nighttime), respectively. The PBL UHI generally exists only in the daytime potentially caused by the thermal convective diffusion. The near-surface and PBL UHIs are significantly affected by the horizontal advection, resulting in different UHI intensities and variations against rural regions in different orientations. Cold advection from the Yangtze River (the ocean) in the riverside (coastal) rural region corresponds to the great UHI intensification, while the strong cold advection in the urban region well explains the fast UHI weakening. This study highlights that, besides local thermal factors, synoptic circulation also play an important role in the interaction between the UHI effect and HW events.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"311 ","pages":"Article 107721"},"PeriodicalIF":4.5,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142417126","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}
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