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Abstract
Recent idealized simulations have shown that a system of binary tropical cyclones (TCs) induces vertical wind shear (VWS) in each TC, which can subsequently modify the tracks of these TCs through asymmetric diabatic heating. This study investigates these three-dimensional effects in the western North Pacific using the best track and ERA5 reanalysis data. The TC motion was found to deviate systematically from the steering flow. The direction of deviation is clockwise and repelling with respect to the midpoint of the binary TCs with a separation distance of more than 1000 km. The large-scale upper-level anticyclonic and lower-level cyclonic circulations serve as the VWS for each TC in a manner consistent with the idealized simulations. The VWS of a TC tends to be directed to the rear-left quadrant from the direction of the counterpart TC, where the maxima of rainfall and diabatic heating are observed. The potential vorticity budget analysis shows that the actual TC motion is modulated by the diabatic heating asymmetry that offsets the counterclockwise and approaching motion owing to horizontal advection when the separation distance of the binary TCs is 1000–2000 km. With a small separation distance (<1000 km), horizontal advection becomes significant, but the impact of diabatic heating asymmetry is not negligible. The abovementioned features are robust, while there are some dependencies on the TC intensities, size, circulation, duration, and geographical location. This research sheds light on the motion of binary TCs that has not been previously explained by a two-dimensional barotropic framework.
Abstract
Recent idealized simulations have shown that a system of binary tropical cyclones (TCs) induces vertical wind shear (VWS) in each TC, which can subsequently modify the tracks of these TCs through asymmetric diabatic heating. This study investigates these three-dimensional effects in the western North Pacific using the best track and ERA5 reanalysis data. The TC motion was found to deviate systematically from the steering flow. The direction of deviation is clockwise and repelling with respect to the midpoint of the binary TCs with a separation distance of more than 1000 km. The large-scale upper-level anticyclonic and lower-level cyclonic circulations serve as the VWS for each TC in a manner consistent with the idealized simulations. The VWS of a TC tends to be directed to the rear-left quadrant from the direction of the counterpart TC, where the maxima of rainfall and diabatic heating are observed. The potential vorticity budget analysis shows that the actual TC motion is modulated by the diabatic heating asymmetry that offsets the counterclockwise and approaching motion owing to horizontal advection when the separation distance of the binary TCs is 1000–2000 km. With a small separation distance (<1000 km), horizontal advection becomes significant, but the impact of diabatic heating asymmetry is not negligible. The abovementioned features are robust, while there are some dependencies on the TC intensities, size, circulation, duration, and geographical location. This research sheds light on the motion of binary TCs that has not been previously explained by a two-dimensional barotropic framework.
Abstract
The Maritime Continent experiences some of the world’s most severe convective rainfall, with an intense diurnal cycle. A key feature is offshore propagation of convection overnight, having peaked over land during the evening. Existing hypotheses suggest this propagation is due to the nocturnal land breeze and environmental wind causing low-level convergence; and/or gravity waves triggering convection as they propagate. We use a convection-permitting configuration of the Met Office Unified Model over Sumatra to test these hypotheses, verifying against observations from the Japanese Years of the Maritime Continent field campaign. In selected case studies there is an organized squall line propagating with the land-breeze density current, possibly reinforced by convective cold pools, at ∼3 m s−1 to around 150–300 km offshore. Propagation at these speeds is also seen in a composite mean diurnal cycle. The density current is verified by observations, with offshore low-level wind and virtual potential temperature showing a rapid decrease consistent with a density current front, accompanied by rainfall. Gravity waves are identified in the model with a typical phase speed of 16 m s−1. They trigger isolated cells of convection, usually farther offshore and with much weaker precipitation than the squall line. Occasionally, the isolated convection may deepen and the rainfall intensify, if the gravity wave interacts with a substantial preexisting perturbation such as shallow cloud. The localized convection triggered by gravity waves does not generally propagate at the wave’s own speed, but this phenomenon may appear as propagation along a wave trajectory in a composite that averages over many days of the diurnal cycle.
Significance Statement
The intense convection experienced by the Maritime Continent causes high-impact weather in the form of heavy precipitation, which can trigger floods and landslides, endangering human life and infrastructure. The geography of the region, with many islands with complex coastlines and orography, means that the spatial and temporal distributions of convection are difficult to predict. This presents challenges for operational forecasters in the region and introduces biases in weather and climate models, which may propagate globally. A key feature of the convection is its diurnal cycle and associated propagation offshore overnight from the islands. Although this phenomenon has been often investigated, there is no strong consensus in the literature on the mechanism or combination of mechanisms responsible. Improving our knowledge of these mechanisms and how they are represented in a convection-permitting model will assist forecasters in understanding how and when the propagation of intense convective storms occurs, and allow model developers to improve biases in numerical weather prediction and climate models.
Abstract
The Maritime Continent experiences some of the world’s most severe convective rainfall, with an intense diurnal cycle. A key feature is offshore propagation of convection overnight, having peaked over land during the evening. Existing hypotheses suggest this propagation is due to the nocturnal land breeze and environmental wind causing low-level convergence; and/or gravity waves triggering convection as they propagate. We use a convection-permitting configuration of the Met Office Unified Model over Sumatra to test these hypotheses, verifying against observations from the Japanese Years of the Maritime Continent field campaign. In selected case studies there is an organized squall line propagating with the land-breeze density current, possibly reinforced by convective cold pools, at ∼3 m s−1 to around 150–300 km offshore. Propagation at these speeds is also seen in a composite mean diurnal cycle. The density current is verified by observations, with offshore low-level wind and virtual potential temperature showing a rapid decrease consistent with a density current front, accompanied by rainfall. Gravity waves are identified in the model with a typical phase speed of 16 m s−1. They trigger isolated cells of convection, usually farther offshore and with much weaker precipitation than the squall line. Occasionally, the isolated convection may deepen and the rainfall intensify, if the gravity wave interacts with a substantial preexisting perturbation such as shallow cloud. The localized convection triggered by gravity waves does not generally propagate at the wave’s own speed, but this phenomenon may appear as propagation along a wave trajectory in a composite that averages over many days of the diurnal cycle.
Significance Statement
The intense convection experienced by the Maritime Continent causes high-impact weather in the form of heavy precipitation, which can trigger floods and landslides, endangering human life and infrastructure. The geography of the region, with many islands with complex coastlines and orography, means that the spatial and temporal distributions of convection are difficult to predict. This presents challenges for operational forecasters in the region and introduces biases in weather and climate models, which may propagate globally. A key feature of the convection is its diurnal cycle and associated propagation offshore overnight from the islands. Although this phenomenon has been often investigated, there is no strong consensus in the literature on the mechanism or combination of mechanisms responsible. Improving our knowledge of these mechanisms and how they are represented in a convection-permitting model will assist forecasters in understanding how and when the propagation of intense convective storms occurs, and allow model developers to improve biases in numerical weather prediction and climate models.
Abstract
The representation of the stratosphere and stratosphere–troposphere coupling processes is evaluated in the subseasonal Global Ensemble Forecast System, version 12 (GEFSv12), hindcasts. The GEFSv12 hindcasts develop systematic stratospheric biases with increasing lead time, including a too strong boreal wintertime stratospheric polar vortex. In the tropical stratosphere, the GEFSv12 winds and temperatures associated with the quasi-biennial oscillation (QBO) tend to decay with lead time such that they underestimate the observed amplitudes; consistently, the QBO-associated mean meridional circulation is too weak. The hindcasts predict extreme polar vortex events (including sudden stratospheric warmings and vortex intensifications) about 13–14 days in advance, and extreme lower-stratospheric eddy heat flux events about 6–10 days in advance. However, GEFSv12’s ability to predict these events is likely affected by its zonal-mean circulation biases, which increases the rates of false alarms and missed detections. Nevertheless, GEFSv12 shows stratosphere–troposphere coupling relationships that agree well with reanalysis and other subseasonal forecast systems. For instance, GEFSv12 reproduces reanalysis relationships between polar vortex strength and the Northern Annular Mode in the troposphere. It also exhibits enhanced weeks 3–5 prediction skill of the North Atlantic Oscillation index when initialized during strong and weak polar vortex states compared to neutral states. Furthermore, GEFSv12 shows significant differences in Madden–Julian oscillation (MJO) amplitudes and enhanced MJO predictive skill in week 4 during easterly versus westerly QBO phases, though these results are sensitive to the level used to define the QBO. Our results provide a baseline from which future GEFS updates may be measured.
Abstract
The representation of the stratosphere and stratosphere–troposphere coupling processes is evaluated in the subseasonal Global Ensemble Forecast System, version 12 (GEFSv12), hindcasts. The GEFSv12 hindcasts develop systematic stratospheric biases with increasing lead time, including a too strong boreal wintertime stratospheric polar vortex. In the tropical stratosphere, the GEFSv12 winds and temperatures associated with the quasi-biennial oscillation (QBO) tend to decay with lead time such that they underestimate the observed amplitudes; consistently, the QBO-associated mean meridional circulation is too weak. The hindcasts predict extreme polar vortex events (including sudden stratospheric warmings and vortex intensifications) about 13–14 days in advance, and extreme lower-stratospheric eddy heat flux events about 6–10 days in advance. However, GEFSv12’s ability to predict these events is likely affected by its zonal-mean circulation biases, which increases the rates of false alarms and missed detections. Nevertheless, GEFSv12 shows stratosphere–troposphere coupling relationships that agree well with reanalysis and other subseasonal forecast systems. For instance, GEFSv12 reproduces reanalysis relationships between polar vortex strength and the Northern Annular Mode in the troposphere. It also exhibits enhanced weeks 3–5 prediction skill of the North Atlantic Oscillation index when initialized during strong and weak polar vortex states compared to neutral states. Furthermore, GEFSv12 shows significant differences in Madden–Julian oscillation (MJO) amplitudes and enhanced MJO predictive skill in week 4 during easterly versus westerly QBO phases, though these results are sensitive to the level used to define the QBO. Our results provide a baseline from which future GEFS updates may be measured.
Abstract
This work describes the extension of the Global Modeling and Assimilation Office (GMAO) observing system simulation experiment (OSSE) framework to use a hybrid four-dimensional ensemble–variational (4D-EnVar) scheme instead of 3D-Var. The original 3D-Var and hybrid 4D-EnVar OSSEs use the same version of the data assimilation system (DAS) so that a direct comparison is possible in terms of the validation with respect to their corresponding real cases. Rather than quantifying the differences between the two data assimilation methodologies, a short intercomparison of upgrading from a 3D to a 4D OSSE is provided to highlight aspects where this change matters to the OSSE community and to identify particular features of data assimilation that can only be explored in a four-dimensional OSSE framework. A short validation of the hybrid 4D-EnVar OSSE shows that conclusions from previous assessments of the 3D-Var OSSE in its ability to mimic the behavior of the real system still hold with the same caveats. Furthermore, some aspects of the ensemble configuration and behavior are discussed along with forecast sensitivity to observation impacts (FSOI). Estimates of error standard deviations are shown to be smaller in the hybrid 4D-EnVar OSSE but with little impact on the character of the error. A discussion on future work directions focuses on exploring the four-dimensional aspect such as the error distribution within the assimilation window or four-dimensional handling of high-temporal density observations.
Abstract
This work describes the extension of the Global Modeling and Assimilation Office (GMAO) observing system simulation experiment (OSSE) framework to use a hybrid four-dimensional ensemble–variational (4D-EnVar) scheme instead of 3D-Var. The original 3D-Var and hybrid 4D-EnVar OSSEs use the same version of the data assimilation system (DAS) so that a direct comparison is possible in terms of the validation with respect to their corresponding real cases. Rather than quantifying the differences between the two data assimilation methodologies, a short intercomparison of upgrading from a 3D to a 4D OSSE is provided to highlight aspects where this change matters to the OSSE community and to identify particular features of data assimilation that can only be explored in a four-dimensional OSSE framework. A short validation of the hybrid 4D-EnVar OSSE shows that conclusions from previous assessments of the 3D-Var OSSE in its ability to mimic the behavior of the real system still hold with the same caveats. Furthermore, some aspects of the ensemble configuration and behavior are discussed along with forecast sensitivity to observation impacts (FSOI). Estimates of error standard deviations are shown to be smaller in the hybrid 4D-EnVar OSSE but with little impact on the character of the error. A discussion on future work directions focuses on exploring the four-dimensional aspect such as the error distribution within the assimilation window or four-dimensional handling of high-temporal density observations.
Abstract
The initiation of thunderstorms in environments characterized by strong wind shear presents a forecast challenge because of the complexities of the interactions between growing cumulus clouds and wind shear. Thunderstorms that develop in such environments are often capable of producing high-impact hazards, highlighting the importance of convection initiation in sheared environments. Although recent research has greatly improved understanding of the structure and evolution of rising thermals in unsheared environments, there remains uncertainty in how wind shear influences the convection initiation process. Two large-eddy simulations (75-m horizontal grid spacing) were performed to study this problem. Convection initiation attempts are forced in the simulations through prescribed surface heat fluxes (the initial boundary layers are statistically horizontally homogeneous and quasi–steady state but contain turbulent eddies as a result of random initial temperature perturbations). The only difference between the two simulations is the presence or absence of wind shear above 2 km. Important differences in the entrainment patterns are present between sheared and unsheared growing cumulus clouds. As found in previous research, the overturning circulation associated with rising thermals drives dynamic entrainment in the unsheared clouds. However, in sheared clouds, wake entrainment resulting from the tilting of environmental vorticity is an important dynamic entrainment pathway. This result has implications for both the structure of sheared growing cumulus clouds and for convection initiation in sheared environments.
Significance Statement
Forecasts of thunderstorm hazards such as tornadoes, hail, and strong winds, require the accurate prediction of when and where thunderstorms form. Unfortunately, predicting thunderstorm formation is not easy, as there are a lot of different factors to consider. One such factor is environmental vertical wind shear, which describes how winds change speed and direction with height. The purpose of this study is to better understand how wind shear impacts developing clouds. Our results demonstrate a specific mechanism, called “wake entrainment,” through which wind shear can weaken developing clouds and potentially prevent them from becoming strong thunderstorms entirely. Understanding this mechanism may be useful for thunderstorm prediction in environments characterized by wind shear.
Abstract
The initiation of thunderstorms in environments characterized by strong wind shear presents a forecast challenge because of the complexities of the interactions between growing cumulus clouds and wind shear. Thunderstorms that develop in such environments are often capable of producing high-impact hazards, highlighting the importance of convection initiation in sheared environments. Although recent research has greatly improved understanding of the structure and evolution of rising thermals in unsheared environments, there remains uncertainty in how wind shear influences the convection initiation process. Two large-eddy simulations (75-m horizontal grid spacing) were performed to study this problem. Convection initiation attempts are forced in the simulations through prescribed surface heat fluxes (the initial boundary layers are statistically horizontally homogeneous and quasi–steady state but contain turbulent eddies as a result of random initial temperature perturbations). The only difference between the two simulations is the presence or absence of wind shear above 2 km. Important differences in the entrainment patterns are present between sheared and unsheared growing cumulus clouds. As found in previous research, the overturning circulation associated with rising thermals drives dynamic entrainment in the unsheared clouds. However, in sheared clouds, wake entrainment resulting from the tilting of environmental vorticity is an important dynamic entrainment pathway. This result has implications for both the structure of sheared growing cumulus clouds and for convection initiation in sheared environments.
Significance Statement
Forecasts of thunderstorm hazards such as tornadoes, hail, and strong winds, require the accurate prediction of when and where thunderstorms form. Unfortunately, predicting thunderstorm formation is not easy, as there are a lot of different factors to consider. One such factor is environmental vertical wind shear, which describes how winds change speed and direction with height. The purpose of this study is to better understand how wind shear impacts developing clouds. Our results demonstrate a specific mechanism, called “wake entrainment,” through which wind shear can weaken developing clouds and potentially prevent them from becoming strong thunderstorms entirely. Understanding this mechanism may be useful for thunderstorm prediction in environments characterized by wind shear.
Abstract
In sensitivity analysis, ensemble sensitivity is defined as the regression coefficients resulting from a simple linear regression of changes of a response function on initial perturbations. One of the interpretations for ensemble sensitivity considers this a simplified version of regression-based adjoint sensitivity called univariate ensemble sensitivity whose derivation involves the so-called diagonal approximation. This approximation, which replaces the analysis error covariance matrix by a diagonal matrix with the same diagonal, helps to avoid inversion of the analysis error covariance, but, at the same time causes confusion in understanding and practical application of ensemble sensitivity. However, some authors have challenged such a controversial interpretation by showing that univariate ensemble sensitivity is multivariate in nature, which raises the necessity for the foundation of ensemble sensitivity. In this study, we have tried to resolve the confusion by establishing a robust foundation for ensemble sensitivity without relying on the controversial diagonality assumption. As employed in some studies, we adopt an impact-based definition for ensemble sensitivity by taking into account probability distributions of analysis perturbations. The mathematical results show that standardized ensemble sensitivity carries in itself three important quantities at the same time: 1) standardized changes of the forecast response with one standard deviation changes of individual state variables, 2) correlations between the forecast response and individual state variables, and 3) the most sensitive analysis perturbation. The theory guarantees validity of ensemble sensitivity, demonstrates its multivariate nature, and explains why ensemble sensitivity is effective in practice.
Abstract
In sensitivity analysis, ensemble sensitivity is defined as the regression coefficients resulting from a simple linear regression of changes of a response function on initial perturbations. One of the interpretations for ensemble sensitivity considers this a simplified version of regression-based adjoint sensitivity called univariate ensemble sensitivity whose derivation involves the so-called diagonal approximation. This approximation, which replaces the analysis error covariance matrix by a diagonal matrix with the same diagonal, helps to avoid inversion of the analysis error covariance, but, at the same time causes confusion in understanding and practical application of ensemble sensitivity. However, some authors have challenged such a controversial interpretation by showing that univariate ensemble sensitivity is multivariate in nature, which raises the necessity for the foundation of ensemble sensitivity. In this study, we have tried to resolve the confusion by establishing a robust foundation for ensemble sensitivity without relying on the controversial diagonality assumption. As employed in some studies, we adopt an impact-based definition for ensemble sensitivity by taking into account probability distributions of analysis perturbations. The mathematical results show that standardized ensemble sensitivity carries in itself three important quantities at the same time: 1) standardized changes of the forecast response with one standard deviation changes of individual state variables, 2) correlations between the forecast response and individual state variables, and 3) the most sensitive analysis perturbation. The theory guarantees validity of ensemble sensitivity, demonstrates its multivariate nature, and explains why ensemble sensitivity is effective in practice.
Abstract
Moisture transport into the Arctic is an important modulator for clouds, radiative forcing, and sea ice change. Transport events—namely, moist-air intrusions—are often associated with Arctic cyclones, and during the summer season we find that the high-latitude land surface is a significant moisture source for intrusions. Summer Arctic cyclones typically originate from the surrounding continental interior and shorelines where during the early stages of intensification the warm sector experiences strong latent heat fluxes from the land surface. In this study, we use multiyear reanalysis data and back-trajectory calculations to quantify the linkages between key continental moisture source regions and water vapor within cyclone-induced intrusions. We also conduct regional soil moisture sensitivity experiments using the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) to diagnose the land surface moisture contribution for an August 2016 Arctic cyclone case. Results from reanalysis show that land regions on average account for more than 30% of the total moist-air intrusion flux at 70°N during summer. COAMPS case-study experiments reaffirm this result, showing that land surface moisture flux on average accounts for 30% of the intrusion water vapor content. COAMPS experiments further reveal that land surface moisture impacts cyclone intensification and moist-air intrusion cloud water vapor. When the regional soil moisture is reduced, intrusion cloud cover is also reduced, resulting in an increase in the surface solar radiation > 90 W m−2. These results demonstrate that the high-latitude land surface plays an important role in the Arctic summer hydrological cycle and may be increasingly impactful as traditionally cold or frozen soils warm.
Significance Statement
The purpose of this study is to better understand to what extent high-latitude land surface moisture flux is entrained into summer Arctic cyclones and their poleward moisture transport. Moisture transport into the Arctic is important for regional clouds, radiative forcing, and sea ice change. Our results show that land surface evaporation augments cyclone-induced moisture transport into the Arctic on average by 30%. Results are important because traditionally cold or partially frozen high-latitude soils continue to warm and exhibit more positive evaporative trends, including areas undergoing permafrost thaw.
Abstract
Moisture transport into the Arctic is an important modulator for clouds, radiative forcing, and sea ice change. Transport events—namely, moist-air intrusions—are often associated with Arctic cyclones, and during the summer season we find that the high-latitude land surface is a significant moisture source for intrusions. Summer Arctic cyclones typically originate from the surrounding continental interior and shorelines where during the early stages of intensification the warm sector experiences strong latent heat fluxes from the land surface. In this study, we use multiyear reanalysis data and back-trajectory calculations to quantify the linkages between key continental moisture source regions and water vapor within cyclone-induced intrusions. We also conduct regional soil moisture sensitivity experiments using the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) to diagnose the land surface moisture contribution for an August 2016 Arctic cyclone case. Results from reanalysis show that land regions on average account for more than 30% of the total moist-air intrusion flux at 70°N during summer. COAMPS case-study experiments reaffirm this result, showing that land surface moisture flux on average accounts for 30% of the intrusion water vapor content. COAMPS experiments further reveal that land surface moisture impacts cyclone intensification and moist-air intrusion cloud water vapor. When the regional soil moisture is reduced, intrusion cloud cover is also reduced, resulting in an increase in the surface solar radiation > 90 W m−2. These results demonstrate that the high-latitude land surface plays an important role in the Arctic summer hydrological cycle and may be increasingly impactful as traditionally cold or frozen soils warm.
Significance Statement
The purpose of this study is to better understand to what extent high-latitude land surface moisture flux is entrained into summer Arctic cyclones and their poleward moisture transport. Moisture transport into the Arctic is important for regional clouds, radiative forcing, and sea ice change. Our results show that land surface evaporation augments cyclone-induced moisture transport into the Arctic on average by 30%. Results are important because traditionally cold or partially frozen high-latitude soils continue to warm and exhibit more positive evaporative trends, including areas undergoing permafrost thaw.
Abstract
Recent research has demonstrated a relationship between convectively coupled Kelvin waves (CCKWs) and tropical cyclogenesis, likely due to the influence of CCKWs on the large-scale environment. However, it remains unclear which environmental factors are most important and how they connect to TC genesis processes. Using a 39-yr database of African easterly waves (AEWs) to create composites of reanalysis and satellite data, it is shown that genesis may be facilitated by CCKW-driven modifications to convection and moisture. First, stand-alone composites of genesis demonstrate the significant role of environmental preconditioning and convective aggregation. A moist static energy variance budget indicates that convective aggregation during genesis is dominated by feedbacks between convection and longwave radiation. These processes begin over two days prior to genesis, supporting previous observational work. Shifting attention to CCKWs, up to 76% of developing AEWs encounter at least one CCKW in their lifetime. An increase in genesis events following convectively active CCKW phases is found, corroborating earlier studies. A decrease in genesis events following convectively suppressed phases is also identified. Using CCKW-centered composites, we show that the convectively active CCKW phases enhance convection and moisture content in the vicinity of AEWs prior to genesis. Furthermore, enhanced convective activity is the main discriminator between AEW–CCKW interactions that result in genesis versus those that do not. This analysis suggests that CCKWs may influence genesis through environmental preconditioning and radiative–convective feedbacks, among other factors. A secondary finding is that AEW attributes as far east as central Africa may be predictive of downstream genesis.
Significance Statement
The purpose of this work is to investigate how one type of atmospheric wave, known as convectively coupled Kelvin waves (CCKWs), impacts the formation (“genesis”) of tropical cyclones. Forecasting of genesis remains a significant challenge, so identifying how CCKWs influence this process could help improve forecasts and give communities greater lead times. Our results show that CCKWs could temporarily make genesis more likely by increasing atmospheric moisture content and convective activity. While not all CCKWs lead to genesis, those that do are associated with a particularly strong increase in convection. This provides a potential tool for forecasters monitoring CCKWs and TC genesis in real time and motivates follow-up work on this topic in numerical models.
Abstract
Recent research has demonstrated a relationship between convectively coupled Kelvin waves (CCKWs) and tropical cyclogenesis, likely due to the influence of CCKWs on the large-scale environment. However, it remains unclear which environmental factors are most important and how they connect to TC genesis processes. Using a 39-yr database of African easterly waves (AEWs) to create composites of reanalysis and satellite data, it is shown that genesis may be facilitated by CCKW-driven modifications to convection and moisture. First, stand-alone composites of genesis demonstrate the significant role of environmental preconditioning and convective aggregation. A moist static energy variance budget indicates that convective aggregation during genesis is dominated by feedbacks between convection and longwave radiation. These processes begin over two days prior to genesis, supporting previous observational work. Shifting attention to CCKWs, up to 76% of developing AEWs encounter at least one CCKW in their lifetime. An increase in genesis events following convectively active CCKW phases is found, corroborating earlier studies. A decrease in genesis events following convectively suppressed phases is also identified. Using CCKW-centered composites, we show that the convectively active CCKW phases enhance convection and moisture content in the vicinity of AEWs prior to genesis. Furthermore, enhanced convective activity is the main discriminator between AEW–CCKW interactions that result in genesis versus those that do not. This analysis suggests that CCKWs may influence genesis through environmental preconditioning and radiative–convective feedbacks, among other factors. A secondary finding is that AEW attributes as far east as central Africa may be predictive of downstream genesis.
Significance Statement
The purpose of this work is to investigate how one type of atmospheric wave, known as convectively coupled Kelvin waves (CCKWs), impacts the formation (“genesis”) of tropical cyclones. Forecasting of genesis remains a significant challenge, so identifying how CCKWs influence this process could help improve forecasts and give communities greater lead times. Our results show that CCKWs could temporarily make genesis more likely by increasing atmospheric moisture content and convective activity. While not all CCKWs lead to genesis, those that do are associated with a particularly strong increase in convection. This provides a potential tool for forecasters monitoring CCKWs and TC genesis in real time and motivates follow-up work on this topic in numerical models.
Abstract
Obtaining a faithful probabilistic depiction of moist convection is complicated by unknown errors in subgrid-scale physical parameterization schemes, invalid assumptions made by data assimilation (DA) techniques, and high system dimensionality. As an initial step toward untangling sources of uncertainty in convective weather regimes, we evaluate a novel Bayesian data assimilation methodology based on particle filtering within a WRF ensemble analysis and forecasting system. Unlike most geophysical DA methods, the particle filter (PF) represents prior and posterior error distributions nonparametrically rather than assuming a Gaussian distribution and can accept any type of likelihood function. This approach is known to reduce bias introduced by Gaussian approximations in low-dimensional and idealized contexts. The form of PF used in this research adopts a dimension-reduction strategy, making it affordable for typical weather applications. The present study examines posterior ensemble members and forecasts for select severe weather events between 2019 and 2020, comparing results from the PF with those from an ensemble Kalman filter (EnKF). We find that assimilating with a PF produces posterior quantities for microphysical variables that are more consistent with model climatology than comparable quantities from an EnKF, which we attribute to a reduction in DA bias. These differences are significant enough to impact the dynamic evolution of convective systems via cold pool strength and propagation, with impacts to forecast verification scores depending on the particular microphysics scheme. Our findings have broad implications for future approaches to the selection of physical parameterization schemes and parameter estimation within preexisting data assimilation frameworks.
Significance Statement
The accurate prediction of severe storms using numerical weather models depends on effective parameterization schemes for small-scale processes and the assimilation of incomplete observational data in a manner that faithfully represents the probabilistic state of the atmosphere. Current generation methods for data assimilation typically assume a standard form for the error distributions of relevant quantities, which can introduce bias that not only hinders numerical prediction, but that can also confound the characterization of errors from the model itself. The current study performs data assimilation using a novel method that does not make such assumptions and explores characteristics of resulting model fields and forecasts that might make such a method useful for improving model parameterization schemes.
Abstract
Obtaining a faithful probabilistic depiction of moist convection is complicated by unknown errors in subgrid-scale physical parameterization schemes, invalid assumptions made by data assimilation (DA) techniques, and high system dimensionality. As an initial step toward untangling sources of uncertainty in convective weather regimes, we evaluate a novel Bayesian data assimilation methodology based on particle filtering within a WRF ensemble analysis and forecasting system. Unlike most geophysical DA methods, the particle filter (PF) represents prior and posterior error distributions nonparametrically rather than assuming a Gaussian distribution and can accept any type of likelihood function. This approach is known to reduce bias introduced by Gaussian approximations in low-dimensional and idealized contexts. The form of PF used in this research adopts a dimension-reduction strategy, making it affordable for typical weather applications. The present study examines posterior ensemble members and forecasts for select severe weather events between 2019 and 2020, comparing results from the PF with those from an ensemble Kalman filter (EnKF). We find that assimilating with a PF produces posterior quantities for microphysical variables that are more consistent with model climatology than comparable quantities from an EnKF, which we attribute to a reduction in DA bias. These differences are significant enough to impact the dynamic evolution of convective systems via cold pool strength and propagation, with impacts to forecast verification scores depending on the particular microphysics scheme. Our findings have broad implications for future approaches to the selection of physical parameterization schemes and parameter estimation within preexisting data assimilation frameworks.
Significance Statement
The accurate prediction of severe storms using numerical weather models depends on effective parameterization schemes for small-scale processes and the assimilation of incomplete observational data in a manner that faithfully represents the probabilistic state of the atmosphere. Current generation methods for data assimilation typically assume a standard form for the error distributions of relevant quantities, which can introduce bias that not only hinders numerical prediction, but that can also confound the characterization of errors from the model itself. The current study performs data assimilation using a novel method that does not make such assumptions and explores characteristics of resulting model fields and forecasts that might make such a method useful for improving model parameterization schemes.
Abstract
Numerous low-level vortices are initiated downwind of the Hoggar Mountains and progress toward the Atlantic coast on the northern path of African easterly waves (AEWs). These vortices occur mostly in July and August and more specifically when the northern position of the Saharan heat low (SHL) generates stronger and vertically expanded easterly winds over the Hoggar Mountains. At synoptic time scales, a composite analysis reveals that vortex initiation and westward motion are also statistically triggered by a reinforcement of these easterly winds by a wide and persistent high pressure anomaly developing around the Strait of Gibraltar and by a weak wave trough approaching from the east. The vortices are generated in the lee of the Hoggar, about 1000 km west of this approaching trough, and intensify rapidly. The evolution of the vortex perturbation is afterward comparable with the known evolution of the AEWs of the northern path and suggest a growth due to dry barotropic and baroclinic processes induced in particular by the strong cyclonic shear between the reinforced easterly winds and the monsoon flow. These results show that vortex genesis promoted by changes in orographic forcing due to the strengthening of easterly winds over the Hoggar Mountains is a source of intensification of the northern path of AEWs in July and August. These results also provide a possible mechanism to explain the role of the SHL and of particular midlatitude intraseasonal disturbances on the intensity of these waves.
Abstract
Numerous low-level vortices are initiated downwind of the Hoggar Mountains and progress toward the Atlantic coast on the northern path of African easterly waves (AEWs). These vortices occur mostly in July and August and more specifically when the northern position of the Saharan heat low (SHL) generates stronger and vertically expanded easterly winds over the Hoggar Mountains. At synoptic time scales, a composite analysis reveals that vortex initiation and westward motion are also statistically triggered by a reinforcement of these easterly winds by a wide and persistent high pressure anomaly developing around the Strait of Gibraltar and by a weak wave trough approaching from the east. The vortices are generated in the lee of the Hoggar, about 1000 km west of this approaching trough, and intensify rapidly. The evolution of the vortex perturbation is afterward comparable with the known evolution of the AEWs of the northern path and suggest a growth due to dry barotropic and baroclinic processes induced in particular by the strong cyclonic shear between the reinforced easterly winds and the monsoon flow. These results show that vortex genesis promoted by changes in orographic forcing due to the strengthening of easterly winds over the Hoggar Mountains is a source of intensification of the northern path of AEWs in July and August. These results also provide a possible mechanism to explain the role of the SHL and of particular midlatitude intraseasonal disturbances on the intensity of these waves.
