Abstract
Entrainment is a key process that can modulate the intensity of supercells, and a better understanding of its impact could help improve forecasts of thunderstorms and the precipitation they produce. In Part III of this series, the three distinct mechanisms of entrainment identified during the mature stage of idealized supercell thunderstorms in Part I (overturning “ribbons” of horizontal vorticity, “disorganized turbulent eddies,” and the “storm-relative airstream”) are examined as the absolute humidity of the environment is decreased. The existence of these mechanisms in a more realistic simulated storm environment is also established. Entrainment is calculated as fluxes of air across the storm core surface; passive fluid tracers help determine the resulting dilution of the storm updraft. Model microphysical rates are used to examine the direct impacts of entrainment on hydrometeors within the storm updraft as well as precipitation that falls to the ground. Results show that as mixed-layer humidity decreases, the “ribbons” and turbulent eddy mechanisms decrease in intensity, but their effects on precipitation production change little. With decreasing humidity in the 3–4 km AGL layer, the storm-relative airstream entrains less humid low-level air into the storm core, decreasing the vertical mass flux, and therefore the precipitation produced by the storm. When the humidity in the mid- to upper troposphere (4–20 km AGL) is decreased, precipitation is significantly reduced, but not due to the effects of the entrained air. Rather, enhanced evaporation and sublimation of falling precipitation decreases the overall precipitation efficiency of the storm.
Abstract
Entrainment is a key process that can modulate the intensity of supercells, and a better understanding of its impact could help improve forecasts of thunderstorms and the precipitation they produce. In Part III of this series, the three distinct mechanisms of entrainment identified during the mature stage of idealized supercell thunderstorms in Part I (overturning “ribbons” of horizontal vorticity, “disorganized turbulent eddies,” and the “storm-relative airstream”) are examined as the absolute humidity of the environment is decreased. The existence of these mechanisms in a more realistic simulated storm environment is also established. Entrainment is calculated as fluxes of air across the storm core surface; passive fluid tracers help determine the resulting dilution of the storm updraft. Model microphysical rates are used to examine the direct impacts of entrainment on hydrometeors within the storm updraft as well as precipitation that falls to the ground. Results show that as mixed-layer humidity decreases, the “ribbons” and turbulent eddy mechanisms decrease in intensity, but their effects on precipitation production change little. With decreasing humidity in the 3–4 km AGL layer, the storm-relative airstream entrains less humid low-level air into the storm core, decreasing the vertical mass flux, and therefore the precipitation produced by the storm. When the humidity in the mid- to upper troposphere (4–20 km AGL) is decreased, precipitation is significantly reduced, but not due to the effects of the entrained air. Rather, enhanced evaporation and sublimation of falling precipitation decreases the overall precipitation efficiency of the storm.
Abstract
The interaction between Typhoon Nepartak (2016) and the upper-tropospheric cold low (UTCL) is simulated to better understand the impact of UTCL on the structural and intensity change of tropical cyclones (TCs). An experiment without UTCL is also performed to highlight the quantitative impacts of UTCL. Furthermore, idealized sensitivity experiments are carried out to further investigate the specific TC–UTCL configurations leading to different interactions. It is shown that a TC interacting with the UTCL is associated with a more axisymmetric inner-core structure and an earlier rapid intensification. Three plausible mechanisms related to the causality between a UTCL and the intensity change of TC are addressed. First, the lower energy expenditure on outflow expansion leads to higher net heat energy and intensification rate. Second, the external eddy forcing reinforces the secondary circulation and promotes further TC development. Ultimately, the shear-induced downward and radial ventilation of the low-entropy air is unexpectedly reduced despite the presence of UTCL, leading to stronger inner-core convections in the upshear quadrants. In general, the TC–UTCL interaction process of Nepartak is favorable for TC intensification owing to the additional positive effect and the reduced negative effect. In addition, results from sensitivity experiments indicate that the most favorable interaction would occur when the UTCL is located to the north or northwest of the TC at a stable and proper distance of about one Rossby radius of deformation of the UTCL.
Abstract
The interaction between Typhoon Nepartak (2016) and the upper-tropospheric cold low (UTCL) is simulated to better understand the impact of UTCL on the structural and intensity change of tropical cyclones (TCs). An experiment without UTCL is also performed to highlight the quantitative impacts of UTCL. Furthermore, idealized sensitivity experiments are carried out to further investigate the specific TC–UTCL configurations leading to different interactions. It is shown that a TC interacting with the UTCL is associated with a more axisymmetric inner-core structure and an earlier rapid intensification. Three plausible mechanisms related to the causality between a UTCL and the intensity change of TC are addressed. First, the lower energy expenditure on outflow expansion leads to higher net heat energy and intensification rate. Second, the external eddy forcing reinforces the secondary circulation and promotes further TC development. Ultimately, the shear-induced downward and radial ventilation of the low-entropy air is unexpectedly reduced despite the presence of UTCL, leading to stronger inner-core convections in the upshear quadrants. In general, the TC–UTCL interaction process of Nepartak is favorable for TC intensification owing to the additional positive effect and the reduced negative effect. In addition, results from sensitivity experiments indicate that the most favorable interaction would occur when the UTCL is located to the north or northwest of the TC at a stable and proper distance of about one Rossby radius of deformation of the UTCL.
Abstract
The scattering properties of aggregates are studied herein. Early aggregates (<7 monomers) of branched planar crystals and mature aggregates (up to 100 monomers) of columns are randomly generated with varying assumptions about the monomer attachment processes and the orientation behavior during collection. The resulting physical properties of the aggregates correspond well with prior in situ and retrieved sizes and shapes. Assumed azimuthally uniform orientations during collection and monomer pivoting upon attachment resulted in flatter and denser aggregates. The column aggregates had lower density and more spherical shapes than the branched planar crystal aggregates. The scattering properties were calculated using the discrete dipole approximation for a set of orientation angles and transformed to spectral coefficients representing modes of orientation angle variability. The zeroth- and second-order coefficients dominate this variability, with the zeroth-order coefficients representing the scattering properties for randomly oriented particles. The second-order coefficients for backscatter showed differences between horizontal and vertical polarization increasing with density, and these coefficients for specific differential phase increase with both mass and density. Similarly, coefficients for the copolar covariance decreased with density. Rapid changes in the contributions to the radar moments from the second-order coefficients from low to moderate density were observed, likely due to the increasing presence of horizontally aligned monomers in the aggregate structure. Differences in how differential reflectivity and correlation coefficient evolve with the orientation distribution parameters suggest that these measurements, along with specific differential phase and reflectivity, provide complementary information about aggregate sizes, shapes, and orientation distributions.
Abstract
The scattering properties of aggregates are studied herein. Early aggregates (<7 monomers) of branched planar crystals and mature aggregates (up to 100 monomers) of columns are randomly generated with varying assumptions about the monomer attachment processes and the orientation behavior during collection. The resulting physical properties of the aggregates correspond well with prior in situ and retrieved sizes and shapes. Assumed azimuthally uniform orientations during collection and monomer pivoting upon attachment resulted in flatter and denser aggregates. The column aggregates had lower density and more spherical shapes than the branched planar crystal aggregates. The scattering properties were calculated using the discrete dipole approximation for a set of orientation angles and transformed to spectral coefficients representing modes of orientation angle variability. The zeroth- and second-order coefficients dominate this variability, with the zeroth-order coefficients representing the scattering properties for randomly oriented particles. The second-order coefficients for backscatter showed differences between horizontal and vertical polarization increasing with density, and these coefficients for specific differential phase increase with both mass and density. Similarly, coefficients for the copolar covariance decreased with density. Rapid changes in the contributions to the radar moments from the second-order coefficients from low to moderate density were observed, likely due to the increasing presence of horizontally aligned monomers in the aggregate structure. Differences in how differential reflectivity and correlation coefficient evolve with the orientation distribution parameters suggest that these measurements, along with specific differential phase and reflectivity, provide complementary information about aggregate sizes, shapes, and orientation distributions.
Abstract
Several studies have reported vertical kinetic energy spectra almost white in horizontal wavenumber space with evidence of two maxima at synoptic scales and mesoscales, leaving the explanation of these maxima open. Processes known to influence the shape of the horizontal kinetic energy spectra include the superposition of quasi-linear inertia–gravity waves (IGWs), quasigeostrophic turbulence, and moist convection. In contrast, vertical kinetic energy has been discussed much less, as measuring vertical velocity remains challenging. This study compares the horizontal and vertical kinetic energy spectra and their relationships in global storm-resolving simulations from the DYAMOND experiment. The consistency of these relationships with linear IGW theory is tested by diagnosing horizontal wind fluctuations associated with IGW modes. Furthermore, it is shown that hydrostatic IGW polarization relations provide a quantitative prediction of the spectral slopes of vertical kinetic energy at large scales and mesoscales, where the intrinsic frequencies are inferred from the linearized vorticity equation. Our results suggest that IGW modes dominate the vertical kinetic energy spectra at most horizontal scales, whereas an incompressible, isotropic scaling of the continuity equation captures the relationship between horizontal and vertical kinetic energy spectra at small scales.
Abstract
Several studies have reported vertical kinetic energy spectra almost white in horizontal wavenumber space with evidence of two maxima at synoptic scales and mesoscales, leaving the explanation of these maxima open. Processes known to influence the shape of the horizontal kinetic energy spectra include the superposition of quasi-linear inertia–gravity waves (IGWs), quasigeostrophic turbulence, and moist convection. In contrast, vertical kinetic energy has been discussed much less, as measuring vertical velocity remains challenging. This study compares the horizontal and vertical kinetic energy spectra and their relationships in global storm-resolving simulations from the DYAMOND experiment. The consistency of these relationships with linear IGW theory is tested by diagnosing horizontal wind fluctuations associated with IGW modes. Furthermore, it is shown that hydrostatic IGW polarization relations provide a quantitative prediction of the spectral slopes of vertical kinetic energy at large scales and mesoscales, where the intrinsic frequencies are inferred from the linearized vorticity equation. Our results suggest that IGW modes dominate the vertical kinetic energy spectra at most horizontal scales, whereas an incompressible, isotropic scaling of the continuity equation captures the relationship between horizontal and vertical kinetic energy spectra at small scales.
Abstract
The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM; IMERG) is a high-resolution gridded precipitation dataset widely used around the world. This study assessed the performance of the half-hourly IMERG v06 Early and Final Runs over a 5-year period versus nineteen high quality surface stations in the Great Lakes region of North America. This assessment not only looked at precipitation occurrence and amount, but also studied the IMERG Quality Index (QI) and errors related to passive microwave (PMW) sources. Analysis of bias in accumulated precipitation amount and precipitation occurrence statistics suggests that IMERG presents various uncertainties with respect to timescale, meteorological season, PMW source, QI, and land surface type. Results indicate that: (1) the cold season’s ( Nov - Apr ) larger relative bias can be mitigated via backward morphing; (2) IMERG 6-hour precipitation amount scored best in the warmest season (JJA) with a consistent overestimation of the frequency bias index - 1 (FBI-1); (3) the performance of five PMW is affected by the season to different degrees; (4) in terms of some metrics, skills do not always enhance with increasing QI; (5) local lake effects lead to higher correlation and equitable threat score (ETS) for the stations closest to the lakes. Results of this study will be beneficial to both developers and users of IMERG precipitation products.
Abstract
The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM; IMERG) is a high-resolution gridded precipitation dataset widely used around the world. This study assessed the performance of the half-hourly IMERG v06 Early and Final Runs over a 5-year period versus nineteen high quality surface stations in the Great Lakes region of North America. This assessment not only looked at precipitation occurrence and amount, but also studied the IMERG Quality Index (QI) and errors related to passive microwave (PMW) sources. Analysis of bias in accumulated precipitation amount and precipitation occurrence statistics suggests that IMERG presents various uncertainties with respect to timescale, meteorological season, PMW source, QI, and land surface type. Results indicate that: (1) the cold season’s ( Nov - Apr ) larger relative bias can be mitigated via backward morphing; (2) IMERG 6-hour precipitation amount scored best in the warmest season (JJA) with a consistent overestimation of the frequency bias index - 1 (FBI-1); (3) the performance of five PMW is affected by the season to different degrees; (4) in terms of some metrics, skills do not always enhance with increasing QI; (5) local lake effects lead to higher correlation and equitable threat score (ETS) for the stations closest to the lakes. Results of this study will be beneficial to both developers and users of IMERG precipitation products.
Abstract
The characteristics of in-storm cooling occurred ahead-of-eye-center are investigated based on a combination of observations and numerical simulations, as well as its sensitivity to tropical cyclone (TC) characteristics and oceanic climatological conditions. A composite of drifter and remote sensing observations from 1979 to 2020 in the North Hemisphere statistically evidences that the percentage of TC-induced ahead-of-eye-center cooling is enhanced remarkably over the coastal ocean than that over the open sea, no matter what the TC intensity, translation speed and pre-storm SST conditions are. Results are statistically similar when the actual ahead-of-eye SST cooling is used. Idealized numerical simulation results show that as the TC center approaches the coastline, the percentage of ahead-of-eye-center cooling increases steadily with the water depth shallowing below 100 meters. This phenomenon may not be caused by strong stratification of the coastal ocean, as previous studies suggested. An ocean heat balance analysis reveals a new mechanism responsible for the enhanced percentage of ahead-of-eye-center cooling near the coast: although the vertical mixing dominates in the surface cooling process over the open sea, broad and intense advection is largely responsible for the rapid increase of percentage of ahead-of-eye-center cooling over the coastal ocean, owing to less cold-water entrainment from below. A series of sensitivity experiments are conducted by varying TC characteristics in terms of intensity, translation speed, radius of maximum wind speed, and ocean characteristics in terms of temperature profiles and slope rates of the shelf. The percentage of ahead-of-eye-center cooling is dependent on the intensity and translation speed of TCs, but showing little sensitivity to other parameters.
Abstract
The characteristics of in-storm cooling occurred ahead-of-eye-center are investigated based on a combination of observations and numerical simulations, as well as its sensitivity to tropical cyclone (TC) characteristics and oceanic climatological conditions. A composite of drifter and remote sensing observations from 1979 to 2020 in the North Hemisphere statistically evidences that the percentage of TC-induced ahead-of-eye-center cooling is enhanced remarkably over the coastal ocean than that over the open sea, no matter what the TC intensity, translation speed and pre-storm SST conditions are. Results are statistically similar when the actual ahead-of-eye SST cooling is used. Idealized numerical simulation results show that as the TC center approaches the coastline, the percentage of ahead-of-eye-center cooling increases steadily with the water depth shallowing below 100 meters. This phenomenon may not be caused by strong stratification of the coastal ocean, as previous studies suggested. An ocean heat balance analysis reveals a new mechanism responsible for the enhanced percentage of ahead-of-eye-center cooling near the coast: although the vertical mixing dominates in the surface cooling process over the open sea, broad and intense advection is largely responsible for the rapid increase of percentage of ahead-of-eye-center cooling over the coastal ocean, owing to less cold-water entrainment from below. A series of sensitivity experiments are conducted by varying TC characteristics in terms of intensity, translation speed, radius of maximum wind speed, and ocean characteristics in terms of temperature profiles and slope rates of the shelf. The percentage of ahead-of-eye-center cooling is dependent on the intensity and translation speed of TCs, but showing little sensitivity to other parameters.
Abstract
The role of time-dependent freezing of ice nucleating particles (INPs) is evaluated with the ‘Aerosol-Cloud’ (AC) model in: 1) deep convection observed over Oklahoma during the Midlatitude Continental Convective Cloud Experiment (MC3E), 2) orographic clouds observed over North California during the Atmospheric Radiation Measurement (ARM) Cloud Aerosol Precipitation Experiment (ACAPEX), and 3) supercooled, stratiform clouds over the UK, observed during the Aerosol Properties, Processes And Influences on the Earth’s climate (APPRAISE) campaign. AC uses the dynamical core of the WRF model and has hybrid bin/bulk microphysics and a 3D mesoscale domain. AC is validated against coincident aircraft, ground-based and satellite observations for all three cases. Filtered concentrations of ice (> 0.1 to 0.2 mm) agree with those observed at all sampled levels.
AC forms ice heterogeneously through condensation, contact, deposition, and immersion freezing. AC predicts the INP activity of various types of aerosol particles with an empirical parameterization (EP), which follows a singular approach (no time dependence). Here, the EP is modified to represent time-dependent INP activity by a purely empirical approach, using our published laboratory observations of time-dependent INP activity.
In all simulated clouds, the inclusion of time dependence increases the predicted INP activity of mineral dust particles by 0.5 to 1 order of magnitude. However, there is little impact on the cloud glaciation because the total ice is mostly (80-90%) from secondary ice production (SIP) at levels warmer than about −36°C. The Hallett-Mossop process and fragmentation in ice-ice collisions together initiate about 70% of the total ice, whereas fragmentation during both raindrop freezing and sublimation contributes < 10%. Overall, total ice concentrations and SIP are unaffected by time-dependent INP activity.
Abstract
The role of time-dependent freezing of ice nucleating particles (INPs) is evaluated with the ‘Aerosol-Cloud’ (AC) model in: 1) deep convection observed over Oklahoma during the Midlatitude Continental Convective Cloud Experiment (MC3E), 2) orographic clouds observed over North California during the Atmospheric Radiation Measurement (ARM) Cloud Aerosol Precipitation Experiment (ACAPEX), and 3) supercooled, stratiform clouds over the UK, observed during the Aerosol Properties, Processes And Influences on the Earth’s climate (APPRAISE) campaign. AC uses the dynamical core of the WRF model and has hybrid bin/bulk microphysics and a 3D mesoscale domain. AC is validated against coincident aircraft, ground-based and satellite observations for all three cases. Filtered concentrations of ice (> 0.1 to 0.2 mm) agree with those observed at all sampled levels.
AC forms ice heterogeneously through condensation, contact, deposition, and immersion freezing. AC predicts the INP activity of various types of aerosol particles with an empirical parameterization (EP), which follows a singular approach (no time dependence). Here, the EP is modified to represent time-dependent INP activity by a purely empirical approach, using our published laboratory observations of time-dependent INP activity.
In all simulated clouds, the inclusion of time dependence increases the predicted INP activity of mineral dust particles by 0.5 to 1 order of magnitude. However, there is little impact on the cloud glaciation because the total ice is mostly (80-90%) from secondary ice production (SIP) at levels warmer than about −36°C. The Hallett-Mossop process and fragmentation in ice-ice collisions together initiate about 70% of the total ice, whereas fragmentation during both raindrop freezing and sublimation contributes < 10%. Overall, total ice concentrations and SIP are unaffected by time-dependent INP activity.
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 non-parametrically 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 — 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 pre-existing data assimilation frameworks.
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 non-parametrically 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 — 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 pre-existing data assimilation frameworks.
Current human-induced warming has led to approximately a 30-fold increase in the occurrence probability of 2021 northwestern Pacific concurrent marine and terrestrial summer heat.
Current human-induced warming has led to approximately a 30-fold increase in the occurrence probability of 2021 northwestern Pacific concurrent marine and terrestrial summer heat.
