Andrew Janiszeski, R. Rauber, Brian F. Jewett, T. J. Zaremba
This paper examines ice particle re-organization by three-dimensional horizontal kinematic flows within the comma head regions of two U.S. East Coast winter storms, and the effect of reorganization on particle concentrations within snowbands in each storm. In these simplified experiments, the kinematic flows are from the initialization of the HRRR model. Ice particles falling through the comma head were started from either 9, 8, or 7 km altitude, spaced every 200 m, and were transported north or northwest, arriving within the north or northwest half of the primary snowband in each storm. The greatest particle concentration enhancement within each band was a factor of 2.32–3.84 for the 16-17 Dec 2020 storm and 1.76–2.32 for the 29-30 January 2022 storm. Trajectory analyses for particles originating at 4 km on the southeast side of the comma head beneath the dry slot showed that this region supplied particles to the south side of the band with particle enhancements of factor of 1.36–2.08 for the 16-17 Dec 2020 storm and 1.04–2.16 for the 29-30 January 2022 storm. Snowfall within the bands had two source regions: 1) on the north/northwestern side, from ice particles falling from the comma head and, 2) on the southeastern side, from particles forming at or below 4 km altitude and transported northwestward by low-level flow off the Atlantic. While the findings give information on the source of particles in the bands, they do not definitively determine the cause of precipitation banding since other factors, such as large-scale ascent and embedded convection, also contribute to snow growth.
{"title":"Re-Organization of Snowfall Beneath Cloud-top within the Comma Head region of two extreme U.S. East Coast winter cyclones","authors":"Andrew Janiszeski, R. Rauber, Brian F. Jewett, T. J. Zaremba","doi":"10.1175/waf-d-23-0184.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0184.1","url":null,"abstract":"\u0000This paper examines ice particle re-organization by three-dimensional horizontal kinematic flows within the comma head regions of two U.S. East Coast winter storms, and the effect of reorganization on particle concentrations within snowbands in each storm. In these simplified experiments, the kinematic flows are from the initialization of the HRRR model. Ice particles falling through the comma head were started from either 9, 8, or 7 km altitude, spaced every 200 m, and were transported north or northwest, arriving within the north or northwest half of the primary snowband in each storm. The greatest particle concentration enhancement within each band was a factor of 2.32–3.84 for the 16-17 Dec 2020 storm and 1.76–2.32 for the 29-30 January 2022 storm. Trajectory analyses for particles originating at 4 km on the southeast side of the comma head beneath the dry slot showed that this region supplied particles to the south side of the band with particle enhancements of factor of 1.36–2.08 for the 16-17 Dec 2020 storm and 1.04–2.16 for the 29-30 January 2022 storm. Snowfall within the bands had two source regions: 1) on the north/northwestern side, from ice particles falling from the comma head and, 2) on the southeastern side, from particles forming at or below 4 km altitude and transported northwestward by low-level flow off the Atlantic. While the findings give information on the source of particles in the bands, they do not definitively determine the cause of precipitation banding since other factors, such as large-scale ascent and embedded convection, also contribute to snow growth.","PeriodicalId":509742,"journal":{"name":"Weather and Forecasting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141354390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kathryn Semmens, R. Carr, B. Montz, Keri Maxfield, Dana M. Tobin, Joshua S. Kastman, James A. Nelson, Kirstin Harnos, Margaret Beetstra, Patrick Painter
There is growing interest in impact-based decision support services to address complex decision-making, especially for winter storm forecasting. Understanding users’ needs for winter storm forecast information is necessary to make such impact-based winter forecasts relevant and useful to the diverse regions affected. A mixed-method social science research study investigated extending the Winter Storm Severity Index (WSSI) (operational for the contiguous United States (CONUS)) to Alaska, with consideration of the distinct needs of Alaskan stakeholders and the Alaskan climate. Data availability differences suggest the need for an Alaska specific WSSI, calling for user feedback to inform the direction of product modifications. Focus groups and surveys in six regions of Alaska provided information on how the WSSI components, definitions and categorization of impacts could align with stakeholder expectations and led to recommendations for the Weather Prediction Center to consider in developing the WSSI Alaska product. Overall, wind (strength and direction) and precipitation are key components to include. Air travel is a critical concern requiring wind and visibility information, while road travel is less emphasized (contrasting with CONUS needs). Special Weather Statements and Winter Storm Warnings are highly valued, and storm trajectory and transition (between precipitation types) information are important contexts for decision-makers. Alaska is accustomed to and prepared for winter impacts but being able to understand how components (wind, snow, ice) contribute to overall impact enhances the ability to respond and mitigate damage effectively. The WSSI adapted for Alaska can help address regional forecast needs, particularly valuable as the climate changes and typical winter conditions become more variable.
{"title":"Winter Storm Severity Index in Alaska: Understanding the Usefulness for Impact-based Winter Weather Severity Forecast Information","authors":"Kathryn Semmens, R. Carr, B. Montz, Keri Maxfield, Dana M. Tobin, Joshua S. Kastman, James A. Nelson, Kirstin Harnos, Margaret Beetstra, Patrick Painter","doi":"10.1175/waf-d-24-0002.1","DOIUrl":"https://doi.org/10.1175/waf-d-24-0002.1","url":null,"abstract":"\u0000There is growing interest in impact-based decision support services to address complex decision-making, especially for winter storm forecasting. Understanding users’ needs for winter storm forecast information is necessary to make such impact-based winter forecasts relevant and useful to the diverse regions affected. A mixed-method social science research study investigated extending the Winter Storm Severity Index (WSSI) (operational for the contiguous United States (CONUS)) to Alaska, with consideration of the distinct needs of Alaskan stakeholders and the Alaskan climate. Data availability differences suggest the need for an Alaska specific WSSI, calling for user feedback to inform the direction of product modifications. Focus groups and surveys in six regions of Alaska provided information on how the WSSI components, definitions and categorization of impacts could align with stakeholder expectations and led to recommendations for the Weather Prediction Center to consider in developing the WSSI Alaska product. Overall, wind (strength and direction) and precipitation are key components to include. Air travel is a critical concern requiring wind and visibility information, while road travel is less emphasized (contrasting with CONUS needs). Special Weather Statements and Winter Storm Warnings are highly valued, and storm trajectory and transition (between precipitation types) information are important contexts for decision-makers. Alaska is accustomed to and prepared for winter impacts but being able to understand how components (wind, snow, ice) contribute to overall impact enhances the ability to respond and mitigate damage effectively. The WSSI adapted for Alaska can help address regional forecast needs, particularly valuable as the climate changes and typical winter conditions become more variable.","PeriodicalId":509742,"journal":{"name":"Weather and Forecasting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141377554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Karl Schneider, Kelly Lombardo, M. Kumjian, Kevin Bowley
Convective snow (CS) presents a significant hazard to motorists and is one of the leading causes of weather-related fatalities on Pennsylvania roadways. Thus, understanding environmental factors promoting CS formation and organization is critical for providing relevant and accurate information to those impacted. Prior research has been limited, mainly focusing on frontal CS bands often called “snow squalls;” thus, these studies do not account for the diversity of CS organizational modes that is frequently observed, highlighting a need for a robust climatology of broader CS events. To identify such events, a novel, radar-based CS detection algorithm was developed and applied to WSR-88D radar data from 10 cold seasons in central Pennsylvania, during which 159 cases were identified. Distinct convective organization modes were identified: linear (frontal) snow squalls, single cells, multicells, and streamer bands. Each algorithm-flagged radar scan containing CS was manually classified as one of these modes. Interestingly, the moststudied frontal mode only occurred < 5% of the time, whereas multicellular modes dominated CS occurrence. Using the times associated with each CS mode, synoptic and local environmental information from model analyses were investigated. Key characteristics of CS environments compared to null cases include a 500-hPa trough in the vicinity, lower-tropospheric conditional instability, and sufficient moisture. Environments favorable for the different CS modes featured statistically significant differences in the 500-hPa trough axis position, surface-based CAPE, and the unstable layer depth, among others. These results provide insights into forecasting CS mode, explicitly presented in a forecasting decision tree.
{"title":"A Radar-Based 10-year Climatology of Convective Snow Events in Central Pennsylvania","authors":"Karl Schneider, Kelly Lombardo, M. Kumjian, Kevin Bowley","doi":"10.1175/waf-d-23-0187.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0187.1","url":null,"abstract":"\u0000Convective snow (CS) presents a significant hazard to motorists and is one of the leading causes of weather-related fatalities on Pennsylvania roadways. Thus, understanding environmental factors promoting CS formation and organization is critical for providing relevant and accurate information to those impacted. Prior research has been limited, mainly focusing on frontal CS bands often called “snow squalls;” thus, these studies do not account for the diversity of CS organizational modes that is frequently observed, highlighting a need for a robust climatology of broader CS events. To identify such events, a novel, radar-based CS detection algorithm was developed and applied to WSR-88D radar data from 10 cold seasons in central Pennsylvania, during which 159 cases were identified. Distinct convective organization modes were identified: linear (frontal) snow squalls, single cells, multicells, and streamer bands. Each algorithm-flagged radar scan containing CS was manually classified as one of these modes. Interestingly, the moststudied frontal mode only occurred < 5% of the time, whereas multicellular modes dominated CS occurrence. Using the times associated with each CS mode, synoptic and local environmental information from model analyses were investigated. Key characteristics of CS environments compared to null cases include a 500-hPa trough in the vicinity, lower-tropospheric conditional instability, and sufficient moisture. Environments favorable for the different CS modes featured statistically significant differences in the 500-hPa trough axis position, surface-based CAPE, and the unstable layer depth, among others. These results provide insights into forecasting CS mode, explicitly presented in a forecasting decision tree.","PeriodicalId":509742,"journal":{"name":"Weather and Forecasting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140373423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Timothy B. Higgins, Aneesh C. Subramanian, Will E. Chapman, D. Lavers, Andrew C. Winters
Accurate forecasts of weather conditions have the potential to mitigate the social and economic damages they cause. To make informed decisions based on forecasts, it is important to determine the extent to which they could be skillful. This study focuses on subseasonal forecasts out to a lead time of four weeks. We examine the differences between the potential predictability, which is computed under the assumption of a “perfect model”, of integrated vapor transport (IVT) and precipitation under extreme conditions in subseasonal forecasts across the northeast Pacific. Our results demonstrate significant forecast skill of extreme IVT and precipitation events (exceeding the 90th percentile) into week 4 for specific areas, particularly when anomalously wet conditions are observed in the true model state. This forecast skill during weeks 3 and 4 is closely associated with a zonal extension of the North Pacific Jet. These findings of the source of skillful subseasonal forecasts over the US West Coast could have implications for water management in these regions susceptible to drought and flooding extremes. Additionally, they may offer valuable insights for governments and industries on the US West Coast seeking to make informed decisions based on extended weather prediction.
{"title":"Subseasonal Potential Predictability of Horizontal Water Vapor Transport and Precipitation Extremes in the North Pacific","authors":"Timothy B. Higgins, Aneesh C. Subramanian, Will E. Chapman, D. Lavers, Andrew C. Winters","doi":"10.1175/waf-d-23-0170.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0170.1","url":null,"abstract":"\u0000Accurate forecasts of weather conditions have the potential to mitigate the social and economic damages they cause. To make informed decisions based on forecasts, it is important to determine the extent to which they could be skillful. This study focuses on subseasonal forecasts out to a lead time of four weeks. We examine the differences between the potential predictability, which is computed under the assumption of a “perfect model”, of integrated vapor transport (IVT) and precipitation under extreme conditions in subseasonal forecasts across the northeast Pacific. Our results demonstrate significant forecast skill of extreme IVT and precipitation events (exceeding the 90th percentile) into week 4 for specific areas, particularly when anomalously wet conditions are observed in the true model state. This forecast skill during weeks 3 and 4 is closely associated with a zonal extension of the North Pacific Jet. These findings of the source of skillful subseasonal forecasts over the US West Coast could have implications for water management in these regions susceptible to drought and flooding extremes. Additionally, they may offer valuable insights for governments and industries on the US West Coast seeking to make informed decisions based on extended weather prediction.","PeriodicalId":509742,"journal":{"name":"Weather and Forecasting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140377063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Legacy National Weather Service verification techniques, when applied to current static severe convective warnings, exhibit limitations, particularly in accounting for the precise spatial and temporal aspects of warnings and severe convective events. Consequently, they are not particularly well-suited for application to some proposed future National Weather Service warning delivery methods considered under the Forecasting a Continuum of Environmental Threats (FACETs) initiative. These methods include Threats-In-Motion (TIM), wherein warning polygons move nearly continuously with convective hazards, and Probabilistic Hazard Information (PHI), a concept that involves augmenting warnings with rapidly updating probabilistic plumes. A new geospatial verification method was developed and evaluated, by which warnings and observations are placed on equivalent grids within a common reference frame, with each grid cell being represented as a hit, miss, false alarm, or correct null for each minute. New measures are computed, including false alarm area, and location-specific lead time, departure time, and false alarm time. Using the 27 April 2011 tornado event, we applied the TIM and PHI warning techniques to demonstrate the benefits of rapidly updating warning areas, showcase the application of the geospatial verification method within this novel warning framework, and highlight the impact of varying probabilistic warning thresholds on warning performance. Additionally, the geospatial verification method was tested on a storm-based warning dataset (2008-2022) to derive annual, monthly, and hourly statistics.
{"title":"A Geospatial Verification Method for Severe Convective Weather Warnings: Implications for Current and Future Warning Methods","authors":"Gregory J. Stumpf, Sarah M. Stough","doi":"10.1175/waf-d-23-0153.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0153.1","url":null,"abstract":"\u0000Legacy National Weather Service verification techniques, when applied to current static severe convective warnings, exhibit limitations, particularly in accounting for the precise spatial and temporal aspects of warnings and severe convective events. Consequently, they are not particularly well-suited for application to some proposed future National Weather Service warning delivery methods considered under the Forecasting a Continuum of Environmental Threats (FACETs) initiative. These methods include Threats-In-Motion (TIM), wherein warning polygons move nearly continuously with convective hazards, and Probabilistic Hazard Information (PHI), a concept that involves augmenting warnings with rapidly updating probabilistic plumes.\u0000A new geospatial verification method was developed and evaluated, by which warnings and observations are placed on equivalent grids within a common reference frame, with each grid cell being represented as a hit, miss, false alarm, or correct null for each minute. New measures are computed, including false alarm area, and location-specific lead time, departure time, and false alarm time.\u0000Using the 27 April 2011 tornado event, we applied the TIM and PHI warning techniques to demonstrate the benefits of rapidly updating warning areas, showcase the application of the geospatial verification method within this novel warning framework, and highlight the impact of varying probabilistic warning thresholds on warning performance. Additionally, the geospatial verification method was tested on a storm-based warning dataset (2008-2022) to derive annual, monthly, and hourly statistics.","PeriodicalId":509742,"journal":{"name":"Weather and Forecasting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140427601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Katherine E. McKeown, Casey E. Davenport, M. Eastin, Sarah M. Purpura, Roger R. Riggin
The evolution of supercell thunderstorms traversing complex terrain is not well understood and remains a short-term forecast challenge across the Appalachian Mountains of the eastern United States. Although case studies have been conducted, there has been no large multi-case observational analysis focusing on the central and southern Appalachians. To address this gap, we analyzed 62 isolated warm-season supercells that occurred in this region. Each supercell was categorized as either crossing (∼40%) or noncrossing (∼60%) based on their maintenance of supercellular structure while traversing prominent terrain. The structural evolution of each storm was analyzed via operationally relevant parameters extracted from WSR-88D radar data. The most significant differences in radar-observed structure among storm categories were associated with the mesocyclone; crossing storms exhibited stronger, wider, and deeper mesocyclones, along with more prominent and persistent hook echoes. Crossing storms also moved faster. Among the supercells that crossed the most prominent peaks and ridges, significant increases in base reflectivity, vertically integrated liquid, echo tops, and mesocyclone intensity/depth were observed, in conjunction with more frequent large hail and tornado reports, as the storms ascended windward slopes. Then, as the supercells descended leeward slopes, significant increases in mesocyclone depth and tornado frequency were observed. Such results reinforce the notion that supercell evolution can be modulated substantially by passage through and over complex terrain.
{"title":"Radar Characteristics of Supercell Thunderstorms Traversing the Appalachian Mountains","authors":"Katherine E. McKeown, Casey E. Davenport, M. Eastin, Sarah M. Purpura, Roger R. Riggin","doi":"10.1175/waf-d-23-0110.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0110.1","url":null,"abstract":"\u0000The evolution of supercell thunderstorms traversing complex terrain is not well understood and remains a short-term forecast challenge across the Appalachian Mountains of the eastern United States. Although case studies have been conducted, there has been no large multi-case observational analysis focusing on the central and southern Appalachians. To address this gap, we analyzed 62 isolated warm-season supercells that occurred in this region. Each supercell was categorized as either crossing (∼40%) or noncrossing (∼60%) based on their maintenance of supercellular structure while traversing prominent terrain. The structural evolution of each storm was analyzed via operationally relevant parameters extracted from WSR-88D radar data. The most significant differences in radar-observed structure among storm categories were associated with the mesocyclone; crossing storms exhibited stronger, wider, and deeper mesocyclones, along with more prominent and persistent hook echoes. Crossing storms also moved faster. Among the supercells that crossed the most prominent peaks and ridges, significant increases in base reflectivity, vertically integrated liquid, echo tops, and mesocyclone intensity/depth were observed, in conjunction with more frequent large hail and tornado reports, as the storms ascended windward slopes. Then, as the supercells descended leeward slopes, significant increases in mesocyclone depth and tornado frequency were observed. Such results reinforce the notion that supercell evolution can be modulated substantially by passage through and over complex terrain.","PeriodicalId":509742,"journal":{"name":"Weather and Forecasting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140425967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study documents the features of tornadoes, their parent storms and the environments of the only two documented tornado outbreak events in China. The two events were associated with tropical cyclone (TC) Yagi on 12 August 2018, with 11 tornadoes, and with an extratropical cyclone (EC) on 11 July 2021 (EC 711), with 13 tornadoes. Most tornadoes in TC Yagi were spawned from discrete mini-supercells, while a majority of tornadoes in EC 711 were produced from supercells imbedded in QLCSs or cloud clusters. In both events, the high-tornado-density area was better collocated with K index rather than MLCAPE, and with entraining rather than non-entraining parameters possibly due to their sensitivity to mid-level moisture. EC 711 had a larger displacement between maximum entraining CAPE and vertical wind shear than TC Yagi, with the maximum entraining CAPE better collocated with the high-tornado-density area than vertical wind shear. Relative to TC Yagi, EC 711 had stronger entraining CAPE, 0–1-km storm relative helicity, 0–6-km vertical wind shear, and composite parameters such as entraining significant tornado parameter, which caused its generally stronger tornado vortex signatures (TVSs) and mesocyclones with a larger diameter and longer lifespan. No significant differences were found in composite parameter of these two events from U.S. statistics. Although obvious dry air intrusions were observed in both events, no apparent impact was observed on the potential of tornado outbreak in EC 711. In TC Yagi, however, the dry air intrusion may have helped tornado outbreak due to cloudiness erosion and thus increase in surface temperature and low-level lapse rate.
{"title":"A Comparison between the Only Two Documented Tornado Outbreak Events in China: Tropical Cyclone vs. Extratropical Cyclone Environments","authors":"Jingyi Wen, Zhiyong Meng, L. Bai, Ruilin Zhou","doi":"10.1175/waf-d-23-0083.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0083.1","url":null,"abstract":"\u0000This study documents the features of tornadoes, their parent storms and the environments of the only two documented tornado outbreak events in China. The two events were associated with tropical cyclone (TC) Yagi on 12 August 2018, with 11 tornadoes, and with an extratropical cyclone (EC) on 11 July 2021 (EC 711), with 13 tornadoes. Most tornadoes in TC Yagi were spawned from discrete mini-supercells, while a majority of tornadoes in EC 711 were produced from supercells imbedded in QLCSs or cloud clusters. In both events, the high-tornado-density area was better collocated with K index rather than MLCAPE, and with entraining rather than non-entraining parameters possibly due to their sensitivity to mid-level moisture. EC 711 had a larger displacement between maximum entraining CAPE and vertical wind shear than TC Yagi, with the maximum entraining CAPE better collocated with the high-tornado-density area than vertical wind shear. Relative to TC Yagi, EC 711 had stronger entraining CAPE, 0–1-km storm relative helicity, 0–6-km vertical wind shear, and composite parameters such as entraining significant tornado parameter, which caused its generally stronger tornado vortex signatures (TVSs) and mesocyclones with a larger diameter and longer lifespan. No significant differences were found in composite parameter of these two events from U.S. statistics. Although obvious dry air intrusions were observed in both events, no apparent impact was observed on the potential of tornado outbreak in EC 711. In TC Yagi, however, the dry air intrusion may have helped tornado outbreak due to cloudiness erosion and thus increase in surface temperature and low-level lapse rate.","PeriodicalId":509742,"journal":{"name":"Weather and Forecasting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140444007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To reduce hurricane intensity bias, the NCEP Global Forecast System (GFS) planetary boundary layer (PBL) and convection schemes have been updated with a new parameterization for environmental wind shear and enhanced entrainment and detrainment rates with increasing PBL or sub-cloud mean turbulent kinetic energy (TKE) in their updraft and downdraft mass-flux schemes. Tests with the GFS show that the updated schemes significantly reduce the hurricane intensity bias by reducing the momentum transport in the mass-flux schemes. Along with the reduced intensity bias, the hurricane intensity and track errors have also been reduced. On the other hand, to reduce the PBL overgrowth over areas with a higher vegetation fraction or larger surface roughness, the entrainment rate in the PBL mass-flux scheme has also been increased with increasing vegetation fraction or increasing surface roughness. This entrainment rate increase has increased near surface moisture, and as a result, helped to increase the underestimated convective available potential energy (CAPE) forecasts over the continental United States.
{"title":"Updates in the NCEP GFS PBL and Convection Models with Environmental Wind Shear Effect and Modified Entrainment and Detrainment Rates and their Impacts on the GFS Hurricane and CAPE Forecasts","authors":"Jongil Han, Jiayi Peng, Wei Li, Weiguo Wang, Zhan Zhang, Fanglin Yang, Weizhong Zheng","doi":"10.1175/waf-d-23-0134.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0134.1","url":null,"abstract":"\u0000To reduce hurricane intensity bias, the NCEP Global Forecast System (GFS) planetary boundary layer (PBL) and convection schemes have been updated with a new parameterization for environmental wind shear and enhanced entrainment and detrainment rates with increasing PBL or sub-cloud mean turbulent kinetic energy (TKE) in their updraft and downdraft mass-flux schemes. Tests with the GFS show that the updated schemes significantly reduce the hurricane intensity bias by reducing the momentum transport in the mass-flux schemes. Along with the reduced intensity bias, the hurricane intensity and track errors have also been reduced. On the other hand, to reduce the PBL overgrowth over areas with a higher vegetation fraction or larger surface roughness, the entrainment rate in the PBL mass-flux scheme has also been increased with increasing vegetation fraction or increasing surface roughness. This entrainment rate increase has increased near surface moisture, and as a result, helped to increase the underestimated convective available potential energy (CAPE) forecasts over the continental United States.","PeriodicalId":509742,"journal":{"name":"Weather and Forecasting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140442213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Hazelton, Xiaomin Chen, G. Alaka, G. Alvey, S. Gopalakrishnan, Frank Marks
Understanding how model physics impact tropical cyclone (TC) structure, motion, and evolution is critical for the development of TC forecast models. This study examines the impacts of microphysics and planetary boundary layer (PBL) physics on forecasts using the Hurricane Analysis and Forecast System (HAFS), which is newly operational in 2023. The “HAFS-B” version is specifically evaluated, and 3 sensitivity tests (for over 400 cases in 15 Atlantic TCs) are compared with retrospective HAFS-B runs. Sensitivity tests are generated by 1) Changing the microphysics in HAFS-B from Thompson to GFDL, 2) turning off the TC-specific PBL modifications that have been implemented in operational HAFS-B, and 3) combining the PBL and microphysics modifications. The forecasts are compared through standard verification metrics, and also examination of composite structure. Verification results show that Thompson microphysics slightly degrades the Day 3-4 forecast track in HAFS-B, but improves forecasts of long-term intensity. The TC-specific PBL changes lead to a reduction in a negative intensity bias and improvement in RI skill, but cause some degradation in prediction of 34-knot wind radii. Composites illustrate slightly deeper vortices in runs with the Thompson microphysics, and stronger PBL inflow with the TC-specific PBL modifications. These combined results demonstrate the critical role of model physics in regulating TC structure and intensity, and point to the need to continue to develop improvements to HAFS physics. The study also shows that the combination of both PBL and microphysics modifications (which are both included in one of the two versions of HAFS in the first operational implementation) leads to the best overall results.
{"title":"Sensitivity of HAFS-B Tropical Cyclone Forecasts to Planetary Boundary Layer and Microphysics Parameterizations","authors":"A. Hazelton, Xiaomin Chen, G. Alaka, G. Alvey, S. Gopalakrishnan, Frank Marks","doi":"10.1175/waf-d-23-0124.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0124.1","url":null,"abstract":"\u0000Understanding how model physics impact tropical cyclone (TC) structure, motion, and evolution is critical for the development of TC forecast models. This study examines the impacts of microphysics and planetary boundary layer (PBL) physics on forecasts using the Hurricane Analysis and Forecast System (HAFS), which is newly operational in 2023. The “HAFS-B” version is specifically evaluated, and 3 sensitivity tests (for over 400 cases in 15 Atlantic TCs) are compared with retrospective HAFS-B runs. Sensitivity tests are generated by 1) Changing the microphysics in HAFS-B from Thompson to GFDL, 2) turning off the TC-specific PBL modifications that have been implemented in operational HAFS-B, and 3) combining the PBL and microphysics modifications. The forecasts are compared through standard verification metrics, and also examination of composite structure. Verification results show that Thompson microphysics slightly degrades the Day 3-4 forecast track in HAFS-B, but improves forecasts of long-term intensity. The TC-specific PBL changes lead to a reduction in a negative intensity bias and improvement in RI skill, but cause some degradation in prediction of 34-knot wind radii. Composites illustrate slightly deeper vortices in runs with the Thompson microphysics, and stronger PBL inflow with the TC-specific PBL modifications. These combined results demonstrate the critical role of model physics in regulating TC structure and intensity, and point to the need to continue to develop improvements to HAFS physics. The study also shows that the combination of both PBL and microphysics modifications (which are both included in one of the two versions of HAFS in the first operational implementation) leads to the best overall results.","PeriodicalId":509742,"journal":{"name":"Weather and Forecasting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139779786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Hazelton, Xiaomin Chen, G. Alaka, G. Alvey, S. Gopalakrishnan, Frank Marks
Understanding how model physics impact tropical cyclone (TC) structure, motion, and evolution is critical for the development of TC forecast models. This study examines the impacts of microphysics and planetary boundary layer (PBL) physics on forecasts using the Hurricane Analysis and Forecast System (HAFS), which is newly operational in 2023. The “HAFS-B” version is specifically evaluated, and 3 sensitivity tests (for over 400 cases in 15 Atlantic TCs) are compared with retrospective HAFS-B runs. Sensitivity tests are generated by 1) Changing the microphysics in HAFS-B from Thompson to GFDL, 2) turning off the TC-specific PBL modifications that have been implemented in operational HAFS-B, and 3) combining the PBL and microphysics modifications. The forecasts are compared through standard verification metrics, and also examination of composite structure. Verification results show that Thompson microphysics slightly degrades the Day 3-4 forecast track in HAFS-B, but improves forecasts of long-term intensity. The TC-specific PBL changes lead to a reduction in a negative intensity bias and improvement in RI skill, but cause some degradation in prediction of 34-knot wind radii. Composites illustrate slightly deeper vortices in runs with the Thompson microphysics, and stronger PBL inflow with the TC-specific PBL modifications. These combined results demonstrate the critical role of model physics in regulating TC structure and intensity, and point to the need to continue to develop improvements to HAFS physics. The study also shows that the combination of both PBL and microphysics modifications (which are both included in one of the two versions of HAFS in the first operational implementation) leads to the best overall results.
{"title":"Sensitivity of HAFS-B Tropical Cyclone Forecasts to Planetary Boundary Layer and Microphysics Parameterizations","authors":"A. Hazelton, Xiaomin Chen, G. Alaka, G. Alvey, S. Gopalakrishnan, Frank Marks","doi":"10.1175/waf-d-23-0124.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0124.1","url":null,"abstract":"\u0000Understanding how model physics impact tropical cyclone (TC) structure, motion, and evolution is critical for the development of TC forecast models. This study examines the impacts of microphysics and planetary boundary layer (PBL) physics on forecasts using the Hurricane Analysis and Forecast System (HAFS), which is newly operational in 2023. The “HAFS-B” version is specifically evaluated, and 3 sensitivity tests (for over 400 cases in 15 Atlantic TCs) are compared with retrospective HAFS-B runs. Sensitivity tests are generated by 1) Changing the microphysics in HAFS-B from Thompson to GFDL, 2) turning off the TC-specific PBL modifications that have been implemented in operational HAFS-B, and 3) combining the PBL and microphysics modifications. The forecasts are compared through standard verification metrics, and also examination of composite structure. Verification results show that Thompson microphysics slightly degrades the Day 3-4 forecast track in HAFS-B, but improves forecasts of long-term intensity. The TC-specific PBL changes lead to a reduction in a negative intensity bias and improvement in RI skill, but cause some degradation in prediction of 34-knot wind radii. Composites illustrate slightly deeper vortices in runs with the Thompson microphysics, and stronger PBL inflow with the TC-specific PBL modifications. These combined results demonstrate the critical role of model physics in regulating TC structure and intensity, and point to the need to continue to develop improvements to HAFS physics. The study also shows that the combination of both PBL and microphysics modifications (which are both included in one of the two versions of HAFS in the first operational implementation) leads to the best overall results.","PeriodicalId":509742,"journal":{"name":"Weather and Forecasting","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139839557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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