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Abstract
This study evaluates the impact of assimilating Global Navigation Satellite System (GNSS) radio occultation (RO) bending angles from Formosa Satellite Mission-7/Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) receiver satellites on Hurricane Weather Research and Forecasting (HWRF) Model tropical cyclone (TC) forecasts. Launched in June 2019, the COSMIC-2 mission provides significantly higher tropics data coverage compared to its predecessor COSMIC constellation. GNSS RO measurements yield information about atmospheric pressure, temperature, and water vapor profiles. HWRF is cycled with and without COSMIC-2 bending angle data assimilation for six 2020 Atlantic hurricane cases. COSMIC-2 assimilation has little impact on HWRF track forecasts, consistent with HWRF’s design limiting cycled data assimilation impacts on surrounding large-scale flows; however, COSMIC-2 assimilation results in a statistically significant ∼8%–12% mean absolute forecast error reduction in minimum central sea level pressure for t = 36-, 54-, 60-, and 108–120-h lead times. Forecasts initialized from analyses assimilating COSMIC-2 observations also have a 1%–4% smaller 600–700-hPa specific humidity (SPFH) root-mean-squared deviation compared to radiosondes and dropwindsondes for most lead times. While not all HWRF intensity forecasts benefit from COSMIC-2 assimilation, a few show notable improvement. For example, assimilating two COSMIC-2 profiles within the inner core of developing Hurricane Hanna (2020) increases 800-hPa SPFH by up to 1 g kg−1 locally, helping to correct a dry bias. The forecast initialized from this analysis better captures Hanna’s observed intensification rate, likely because its moister inner core facilitates development of persistent deep convection near the TC center, where diabatic heating is more efficiently converted to cyclonic wind kinetic energy.
Significance Statement
Tropical cyclone (TC) intensification can be strongly sensitive to the lower-to-midtropospheric water vapor distribution near the storm. The COSMIC-2 GNSS radio occultation (RO) receiver satellite mission provides denser spatial coverage of atmospheric water vapor and temperature profiles over the tropics compared to other GNSS RO observation platforms. Herein, using six 2020 Atlantic TC cases, we evaluate the impacts of assimilating COSMIC-2 RO bending angles into a regional forecast model that already assimilates clear-sky satellite radiances. It is shown that COSMIC-2 assimilation yields a modest ∼10% intensity forecast skill improvement for several lead times, although more substantial intensity forecast improvement is found for a few forecasts where the COSMIC-2 observation assimilation helps correct a lower-to-midtropospheric water vapor bias.
Abstract
This study evaluates the impact of assimilating Global Navigation Satellite System (GNSS) radio occultation (RO) bending angles from Formosa Satellite Mission-7/Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) receiver satellites on Hurricane Weather Research and Forecasting (HWRF) Model tropical cyclone (TC) forecasts. Launched in June 2019, the COSMIC-2 mission provides significantly higher tropics data coverage compared to its predecessor COSMIC constellation. GNSS RO measurements yield information about atmospheric pressure, temperature, and water vapor profiles. HWRF is cycled with and without COSMIC-2 bending angle data assimilation for six 2020 Atlantic hurricane cases. COSMIC-2 assimilation has little impact on HWRF track forecasts, consistent with HWRF’s design limiting cycled data assimilation impacts on surrounding large-scale flows; however, COSMIC-2 assimilation results in a statistically significant ∼8%–12% mean absolute forecast error reduction in minimum central sea level pressure for t = 36-, 54-, 60-, and 108–120-h lead times. Forecasts initialized from analyses assimilating COSMIC-2 observations also have a 1%–4% smaller 600–700-hPa specific humidity (SPFH) root-mean-squared deviation compared to radiosondes and dropwindsondes for most lead times. While not all HWRF intensity forecasts benefit from COSMIC-2 assimilation, a few show notable improvement. For example, assimilating two COSMIC-2 profiles within the inner core of developing Hurricane Hanna (2020) increases 800-hPa SPFH by up to 1 g kg−1 locally, helping to correct a dry bias. The forecast initialized from this analysis better captures Hanna’s observed intensification rate, likely because its moister inner core facilitates development of persistent deep convection near the TC center, where diabatic heating is more efficiently converted to cyclonic wind kinetic energy.
Significance Statement
Tropical cyclone (TC) intensification can be strongly sensitive to the lower-to-midtropospheric water vapor distribution near the storm. The COSMIC-2 GNSS radio occultation (RO) receiver satellite mission provides denser spatial coverage of atmospheric water vapor and temperature profiles over the tropics compared to other GNSS RO observation platforms. Herein, using six 2020 Atlantic TC cases, we evaluate the impacts of assimilating COSMIC-2 RO bending angles into a regional forecast model that already assimilates clear-sky satellite radiances. It is shown that COSMIC-2 assimilation yields a modest ∼10% intensity forecast skill improvement for several lead times, although more substantial intensity forecast improvement is found for a few forecasts where the COSMIC-2 observation assimilation helps correct a lower-to-midtropospheric water vapor bias.
Abstract
Accurate atmospheric-state analysis is essential for understanding and prediction of the atmosphere and is a difficult scientific problem due to the chaotic nature of the atmosphere; namely, small atmospheric perturbations (APs) grow rapidly in nonlinear processes. The key to atmospheric-state analysis is knowing the structure of the APs. We analyzed the AP structure in terms of network theory using a 192-member AP ensemble. The AP ensemble was generated by an ensemble of variational data assimilation (DA) with the perturbed observation method using the operational numerical weather prediction system at the Japan Meteorological Agency. The generated APs captured flow-dependent AP structures corresponding to atmospheric normal modes, and their use in DA improved accuracy of atmospheric-state predictions. These show the usefulness of the APs. The network property of the APs are as follows. The atmosphere has a small average network distance compared with the square root of the number of nodes, and a large clustering coefficient (about 0.6). These show that the APs have small-world network properties. The degree distribution of APs shows the heavy-tailed structure. These three properties of APs are common to various complex networks in other systems. Hubs in the AP network correspond to atmospheric disturbances. The network community detection using network modularity shows about 18 communities with 0.8 modularity. These basic network properties of APs represent efficient information exchange in the atmosphere, which provides a complementary atmospheric picture to its traditional physical picture based on fluid dynamics and thermodynamics, and would be basic information for atmospheric sciences and extension of application target of the network theory.
Significance Statement
The purpose of this paper is to analyze properties of atmospheric perturbations using the network theory and an accurate ensemble of the atmospheric perturbations. This is important for atmospheric-state estimation and forecasting because the atmosphere is chaotic and small perturbations grow rapidly. Our results show that the atmosphere has a small average network distance and a large clustering coefficient, which are the properties of a small-world network, and a heavy-tailed degree distribution. These three properties of atmospheric perturbations are common to various complex networks in other systems.
Abstract
Accurate atmospheric-state analysis is essential for understanding and prediction of the atmosphere and is a difficult scientific problem due to the chaotic nature of the atmosphere; namely, small atmospheric perturbations (APs) grow rapidly in nonlinear processes. The key to atmospheric-state analysis is knowing the structure of the APs. We analyzed the AP structure in terms of network theory using a 192-member AP ensemble. The AP ensemble was generated by an ensemble of variational data assimilation (DA) with the perturbed observation method using the operational numerical weather prediction system at the Japan Meteorological Agency. The generated APs captured flow-dependent AP structures corresponding to atmospheric normal modes, and their use in DA improved accuracy of atmospheric-state predictions. These show the usefulness of the APs. The network property of the APs are as follows. The atmosphere has a small average network distance compared with the square root of the number of nodes, and a large clustering coefficient (about 0.6). These show that the APs have small-world network properties. The degree distribution of APs shows the heavy-tailed structure. These three properties of APs are common to various complex networks in other systems. Hubs in the AP network correspond to atmospheric disturbances. The network community detection using network modularity shows about 18 communities with 0.8 modularity. These basic network properties of APs represent efficient information exchange in the atmosphere, which provides a complementary atmospheric picture to its traditional physical picture based on fluid dynamics and thermodynamics, and would be basic information for atmospheric sciences and extension of application target of the network theory.
Significance Statement
The purpose of this paper is to analyze properties of atmospheric perturbations using the network theory and an accurate ensemble of the atmospheric perturbations. This is important for atmospheric-state estimation and forecasting because the atmosphere is chaotic and small perturbations grow rapidly. Our results show that the atmosphere has a small average network distance and a large clustering coefficient, which are the properties of a small-world network, and a heavy-tailed degree distribution. These three properties of atmospheric perturbations are common to various complex networks in other systems.
Abstract
A set of control parameters is introduced in the fully elastic nonhydrostatic Euler equations formulated in the mass-based vertical coordinate of Laprise. Contrary to the classical approach, the hydrostatic limit is represented by a subspace of control parameters, instead of a single point. By finding a suitable path from the fully compressible equations to the hydrostatic subspace, we are able to construct a blended system with acoustic modes slowed down and gravity modes nearly unaffected. Numerical stability of the discretized system is thus improved, and the solution remains essentially the fully compressible one. Alternatively, control parameters can be used to redefine the linear model of the constant coefficients semi-implicit time scheme, increasing the numerical stability of the fully compressible system. With a careful choice of the control parameters in both, the linear model used in the semi-implicit temporal scheme, and in the full model, the blended system does not deteriorate the compressible solution while its semi-implicit temporal discretization is more stable. We illustrate the potential of the method in several simple examples and in real case studies using the ALADIN system.
Abstract
A set of control parameters is introduced in the fully elastic nonhydrostatic Euler equations formulated in the mass-based vertical coordinate of Laprise. Contrary to the classical approach, the hydrostatic limit is represented by a subspace of control parameters, instead of a single point. By finding a suitable path from the fully compressible equations to the hydrostatic subspace, we are able to construct a blended system with acoustic modes slowed down and gravity modes nearly unaffected. Numerical stability of the discretized system is thus improved, and the solution remains essentially the fully compressible one. Alternatively, control parameters can be used to redefine the linear model of the constant coefficients semi-implicit time scheme, increasing the numerical stability of the fully compressible system. With a careful choice of the control parameters in both, the linear model used in the semi-implicit temporal scheme, and in the full model, the blended system does not deteriorate the compressible solution while its semi-implicit temporal discretization is more stable. We illustrate the potential of the method in several simple examples and in real case studies using the ALADIN system.
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.
