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Abstract
Two cases of observed widespread moderate-or-greater (MOG) clear-air turbulence (CAT) in different synoptic patterns are investigated using a nested high-resolution NWP model. Both of these cases occurred in confluent entrance regions of upper-tropospheric–lower-stratospheric (UTLS) jet streaks, where large-scale anticyclonic outflow from distant organized moist convection strengthened the UTLS jet. Both the strength and vertical sharpness of the resulting jet influence the altitudes of MOG turbulence and the details of simulated turbulence onset mechanisms. In a strong and narrow UTLS jet downstream of a weak synoptic ridge, MOG turbulence arises from Kelvin–Helmholtz (KH) waves that overturn in opposite directions on the vertical flanks of the jet. In broader UTLS jets, MOG turbulence arising from KH waves was favored in strong vertical shear layers beneath the wind maximum, but was inhibited above it due to static stability increases near the tropopause. However, vertically propagating internal gravity waves initiated above KH wave breaking beneath the UTLS jet amplify within the lower stratosphere above the jet, constituting another possible source of turbulence. Turbulence onset mechanisms were often apparent in simulations with minimum horizontal grid spacings of Δx = 1 km. However, amplitudes of the associated grid-resolved vertical motions were unreliable when compared with simulations having minimum horizontal grid spacings of Δx = 1/3 km. In spite of this, turbulence forecasting systems driven by input from coarser-resolution operational NWP models are demonstrated to provide good diagnoses of this type of convectively influenced CAT when the NWP model accurately forecasts upstream convection.
Significance Statement
In this study we document the role of distant convection on observed widespread strong clear-air turbulence near upper-level jet streams in different weather patterns. Results from nested NWP model simulations, together with similar examples from previous case studies, suggest a strong association of widespread turbulence with jet stream enhancements related to outflow from upstream convection. We also demonstrate how model horizontal grid spacings of <1 km are required to adequately resolve common turbulence onset mechanisms (e.g., Kelvin–Helmholtz instability, gravity wave breaking). Nevertheless, examples are provided showing that turbulence forecasting systems driven by lower-resolution operational NWP models can provide potentially valuable guidance on these widespread turbulence events when those models accurately forecast the timing and locations of upstream convection.
Abstract
Two cases of observed widespread moderate-or-greater (MOG) clear-air turbulence (CAT) in different synoptic patterns are investigated using a nested high-resolution NWP model. Both of these cases occurred in confluent entrance regions of upper-tropospheric–lower-stratospheric (UTLS) jet streaks, where large-scale anticyclonic outflow from distant organized moist convection strengthened the UTLS jet. Both the strength and vertical sharpness of the resulting jet influence the altitudes of MOG turbulence and the details of simulated turbulence onset mechanisms. In a strong and narrow UTLS jet downstream of a weak synoptic ridge, MOG turbulence arises from Kelvin–Helmholtz (KH) waves that overturn in opposite directions on the vertical flanks of the jet. In broader UTLS jets, MOG turbulence arising from KH waves was favored in strong vertical shear layers beneath the wind maximum, but was inhibited above it due to static stability increases near the tropopause. However, vertically propagating internal gravity waves initiated above KH wave breaking beneath the UTLS jet amplify within the lower stratosphere above the jet, constituting another possible source of turbulence. Turbulence onset mechanisms were often apparent in simulations with minimum horizontal grid spacings of Δx = 1 km. However, amplitudes of the associated grid-resolved vertical motions were unreliable when compared with simulations having minimum horizontal grid spacings of Δx = 1/3 km. In spite of this, turbulence forecasting systems driven by input from coarser-resolution operational NWP models are demonstrated to provide good diagnoses of this type of convectively influenced CAT when the NWP model accurately forecasts upstream convection.
Significance Statement
In this study we document the role of distant convection on observed widespread strong clear-air turbulence near upper-level jet streams in different weather patterns. Results from nested NWP model simulations, together with similar examples from previous case studies, suggest a strong association of widespread turbulence with jet stream enhancements related to outflow from upstream convection. We also demonstrate how model horizontal grid spacings of <1 km are required to adequately resolve common turbulence onset mechanisms (e.g., Kelvin–Helmholtz instability, gravity wave breaking). Nevertheless, examples are provided showing that turbulence forecasting systems driven by lower-resolution operational NWP models can provide potentially valuable guidance on these widespread turbulence events when those models accurately forecast the timing and locations of upstream convection.
Abstract
One potential way to improve the skill of medium-range weather forecasts is to improve the evolution of Rossby waves, which largely modulate extratropical weather. Recent research has hypothesized that the predictability of downstream Rossby waves may be limited by forecast uncertainty linked to upstream diabatic processes such as latent heat release within the warm conveyor belt (WCB) of extratropical cyclones. This hypothesis is evaluated using Model for Prediction Across Scales (MPAS) ensemble forecasts for two events characterized by highly amplified flow over the North Atlantic associated with cyclogenesis. The source of variability in ridge forecasts is diagnosed using the ensemble-sensitivity technique and a potential vorticity (PV) tendency budget, which quantifies the contribution from individual physical processes toward subsequent ridge amplification. Before the onset of ridge amplitude differences for both events, ensemble forecasts with a more amplified ridge are associated with greater negative PV advection by the irrotational wind. The importance of PV advection by the irrotational wind suggests that PV changes are modulated by diabatic heating, which is confirmed by the sensitivity of ridge amplitude to earlier diabatic heating and lower-tropospheric moisture within an upstream WCB. After the onset of ridge amplitude differences, PV advection by the nondivergent wind becomes the primary driver of downstream forecast differences. Initial condition perturbations within the sensitive areas of the WCB confirm that increasing the initial lower-tropospheric moisture results in a more amplified ridge. This suggests that more accurate initial conditions near the WCB could lead to better downstream forecasts.
Abstract
One potential way to improve the skill of medium-range weather forecasts is to improve the evolution of Rossby waves, which largely modulate extratropical weather. Recent research has hypothesized that the predictability of downstream Rossby waves may be limited by forecast uncertainty linked to upstream diabatic processes such as latent heat release within the warm conveyor belt (WCB) of extratropical cyclones. This hypothesis is evaluated using Model for Prediction Across Scales (MPAS) ensemble forecasts for two events characterized by highly amplified flow over the North Atlantic associated with cyclogenesis. The source of variability in ridge forecasts is diagnosed using the ensemble-sensitivity technique and a potential vorticity (PV) tendency budget, which quantifies the contribution from individual physical processes toward subsequent ridge amplification. Before the onset of ridge amplitude differences for both events, ensemble forecasts with a more amplified ridge are associated with greater negative PV advection by the irrotational wind. The importance of PV advection by the irrotational wind suggests that PV changes are modulated by diabatic heating, which is confirmed by the sensitivity of ridge amplitude to earlier diabatic heating and lower-tropospheric moisture within an upstream WCB. After the onset of ridge amplitude differences, PV advection by the nondivergent wind becomes the primary driver of downstream forecast differences. Initial condition perturbations within the sensitive areas of the WCB confirm that increasing the initial lower-tropospheric moisture results in a more amplified ridge. This suggests that more accurate initial conditions near the WCB could lead to better downstream forecasts.
Abstract
Several studies have documented the sensitivity of convective storm simulations to the microphysics parameterization, but there is less research documenting how these sensitivities change with environmental conditions. In this study, the influence of the lifting condensation level (LCL) on the sensitivity of simulated ordinary convective storm cold pools to the microphysics parameterization is examined. To do this, seven perturbed-microphysics ensembles with nine members each are used, where each ensemble uses a different base state with a surface-based LCL between 500 and 2000 m. A comparison of ensemble standard deviations of cold-pool properties shows a clear trend of increasing sensitivity to the microphysics as the LCL is raised. In physical terms, this trend is the result of lower relative humidities in high-LCL environments that increase low-level rain evaporational cooling rates, which magnifies differences in evaporation already present among the members of a given ensemble owing to the microphysics variations. Omitting supersaturation from the calculation of rain evaporation so that only the raindrop size distribution influences evaporation leads to more evaporation in the low-LCL simulations (owing to more drops), as well as a slightly larger spread in evaporational cooling amounts between members in the low-LCL ensembles. Cold pools in the low-LCL environments are also found to develop earlier and are initially more sensitive to raindrop breakup owing to a larger warm-cloud depth. Altogether, these results suggest that convective storms may be more predictable in low-LCL environments, and forecasts of convection in high-LCL environments may benefit the most from microphysics perturbations within an ensemble forecasting system.
Significance Statement
Computer simulations of thunderstorms can have grid spacings ranging from tens to thousands of meters. Because individual precipitation particles form on scales smaller than these grid spacings, the bulk effects of precipitation processes in models must be approximated. Past studies have found that models are sensitive to these approximations. In this study, we test whether the sensitivity to these approximations changes with the relative humidity in the lowest 1–2 km of the atmosphere. We found that increasing the relative humidity decreases the sensitivity of simulations to the precipitation process approximations. These results can inform meteorologists about the uncertainties surrounding computer-generated thunderstorm forecasts and suggest environmental conditions where using several computer models with different precipitation process approximations may be beneficial.
Abstract
Several studies have documented the sensitivity of convective storm simulations to the microphysics parameterization, but there is less research documenting how these sensitivities change with environmental conditions. In this study, the influence of the lifting condensation level (LCL) on the sensitivity of simulated ordinary convective storm cold pools to the microphysics parameterization is examined. To do this, seven perturbed-microphysics ensembles with nine members each are used, where each ensemble uses a different base state with a surface-based LCL between 500 and 2000 m. A comparison of ensemble standard deviations of cold-pool properties shows a clear trend of increasing sensitivity to the microphysics as the LCL is raised. In physical terms, this trend is the result of lower relative humidities in high-LCL environments that increase low-level rain evaporational cooling rates, which magnifies differences in evaporation already present among the members of a given ensemble owing to the microphysics variations. Omitting supersaturation from the calculation of rain evaporation so that only the raindrop size distribution influences evaporation leads to more evaporation in the low-LCL simulations (owing to more drops), as well as a slightly larger spread in evaporational cooling amounts between members in the low-LCL ensembles. Cold pools in the low-LCL environments are also found to develop earlier and are initially more sensitive to raindrop breakup owing to a larger warm-cloud depth. Altogether, these results suggest that convective storms may be more predictable in low-LCL environments, and forecasts of convection in high-LCL environments may benefit the most from microphysics perturbations within an ensemble forecasting system.
Significance Statement
Computer simulations of thunderstorms can have grid spacings ranging from tens to thousands of meters. Because individual precipitation particles form on scales smaller than these grid spacings, the bulk effects of precipitation processes in models must be approximated. Past studies have found that models are sensitive to these approximations. In this study, we test whether the sensitivity to these approximations changes with the relative humidity in the lowest 1–2 km of the atmosphere. We found that increasing the relative humidity decreases the sensitivity of simulations to the precipitation process approximations. These results can inform meteorologists about the uncertainties surrounding computer-generated thunderstorm forecasts and suggest environmental conditions where using several computer models with different precipitation process approximations may be beneficial.
Abstract
Post-tropical cyclones (PTCs) can bring high winds and extreme precipitation to Europe. Although the structure and intensity of observed Europe-impacting PTCs has been investigated in previous studies, a quantitative understanding of the factors important for PTCs to reach Europe has not been established. By tracking and identifying the full life cycle of tropical cyclones (TCs) in the ERA5 reanalysis, we investigate why some PTCs impact Europe and why others do not, using a composite analysis. We show that PTCs that impact Europe are typically ∼4–6 m s−1 stronger at their lifetime maximum intensity and throughout the extratropical transition process. They are also twice as likely to reintensify in the midlatitudes. During ET, the Europe-impacting PTCs interact more strongly with an upstream upper-level trough in a significantly more baroclinic environment. The Europe-impacting PTCs are steered on a more poleward trajectory across a midlatitude jet streak. It is during the crossing of the jet that these cyclones often undergo their reintensification. Using contingency table analysis, TC lifetime maximum intensity, and whether post-ET reintensification occurs are shown to be significantly associated with the odds that a PTC reaches Europe. This supports our composite analysis and further indicates that TC intensity and reintensification both modulate the likelihood that a PTC will impact Europe.
Significance Statement
Some post-tropical cyclones (PTCs) reach Europe, often associated with extreme precipitation and high winds. It is currently unclear what factors allow this to occur. In this study, we track cyclones in two reanalyses using a feature tracking scheme and identify the PTCs by matching (in space and time) reanalysis tracks with observed tracks. Using a composite analysis, we show that 1) tropical cyclones (TCs) that are more intense, and 2) TCs that reintensify after extratropical transition, are more likely to reach Europe. TCs that reintensify interact strongly with an upper-level upstream trough and cross a midlatitude jet streak. Reintensification occurs as the cyclones cross this jet streak.
Abstract
Post-tropical cyclones (PTCs) can bring high winds and extreme precipitation to Europe. Although the structure and intensity of observed Europe-impacting PTCs has been investigated in previous studies, a quantitative understanding of the factors important for PTCs to reach Europe has not been established. By tracking and identifying the full life cycle of tropical cyclones (TCs) in the ERA5 reanalysis, we investigate why some PTCs impact Europe and why others do not, using a composite analysis. We show that PTCs that impact Europe are typically ∼4–6 m s−1 stronger at their lifetime maximum intensity and throughout the extratropical transition process. They are also twice as likely to reintensify in the midlatitudes. During ET, the Europe-impacting PTCs interact more strongly with an upstream upper-level trough in a significantly more baroclinic environment. The Europe-impacting PTCs are steered on a more poleward trajectory across a midlatitude jet streak. It is during the crossing of the jet that these cyclones often undergo their reintensification. Using contingency table analysis, TC lifetime maximum intensity, and whether post-ET reintensification occurs are shown to be significantly associated with the odds that a PTC reaches Europe. This supports our composite analysis and further indicates that TC intensity and reintensification both modulate the likelihood that a PTC will impact Europe.
Significance Statement
Some post-tropical cyclones (PTCs) reach Europe, often associated with extreme precipitation and high winds. It is currently unclear what factors allow this to occur. In this study, we track cyclones in two reanalyses using a feature tracking scheme and identify the PTCs by matching (in space and time) reanalysis tracks with observed tracks. Using a composite analysis, we show that 1) tropical cyclones (TCs) that are more intense, and 2) TCs that reintensify after extratropical transition, are more likely to reach Europe. TCs that reintensify interact strongly with an upper-level upstream trough and cross a midlatitude jet streak. Reintensification occurs as the cyclones cross this jet streak.
Abstract
This study uses the Weather Research and Forecasting (WRF) Model to investigate the performance of hail parameterizations of the WRF double-moment 7-class (WDM7), aerosol-aware Thompson (AAT), and National Taiwan University triple-moment (NTU3M) bulk microphysics schemes (BMSs) on a real case of a hailstorm initiated in Shandong Province, China. The maximum hail size is particularly evaluated because it is crucial to hail severity prediction, along with areal coverage and intensity of the 24-h solid precipitation during the simulations. Compared with the radar-derived maximum hail size, the objective analysis shows that the NTU3M scheme has the best score in the forecast skill of hail-fall coverage and size, while two BMSs with single-moment rimed ice species overestimate hail diameters aloft but underpredict the coverage at the surface. A deeper investigation suggests that the derived size tendencies from the three BMSs are comparable to the benchmark solutions from the detailed hailstone growth and melting models. The NTU3M scheme displays the most consistent size tendency of the maximum diameter with the benchmark solution in the growth processes. The behaviors of melted diameter by parameterizations are highly related to the treatments of number concentration, which are consistent with the predicted hail severity and coverage. Finally, the sensitivity study shows that increasing the model resolution does not improve the forecast of the maximum hail size, given the biases in the hail mass budget equations and the parameterization of particle size distribution, with single-moment rimed ice species of the AAT scheme.
Significance Statement
Improving hail-forecasting skill, including the size, severity, and the spatial and temporal coverage of hail fall, has become an important subject for numerical weather prediction models as the model resolution increases. The objective of this study is to investigate the fundamental differences in hail parameterizations of three bulk microphysics schemes that lead to differences in the prediction of severe hail events and the spatial coverage of hail fall, hopefully providing insights into hail prediction with a regional numerical weather prediction model in the future.
Abstract
This study uses the Weather Research and Forecasting (WRF) Model to investigate the performance of hail parameterizations of the WRF double-moment 7-class (WDM7), aerosol-aware Thompson (AAT), and National Taiwan University triple-moment (NTU3M) bulk microphysics schemes (BMSs) on a real case of a hailstorm initiated in Shandong Province, China. The maximum hail size is particularly evaluated because it is crucial to hail severity prediction, along with areal coverage and intensity of the 24-h solid precipitation during the simulations. Compared with the radar-derived maximum hail size, the objective analysis shows that the NTU3M scheme has the best score in the forecast skill of hail-fall coverage and size, while two BMSs with single-moment rimed ice species overestimate hail diameters aloft but underpredict the coverage at the surface. A deeper investigation suggests that the derived size tendencies from the three BMSs are comparable to the benchmark solutions from the detailed hailstone growth and melting models. The NTU3M scheme displays the most consistent size tendency of the maximum diameter with the benchmark solution in the growth processes. The behaviors of melted diameter by parameterizations are highly related to the treatments of number concentration, which are consistent with the predicted hail severity and coverage. Finally, the sensitivity study shows that increasing the model resolution does not improve the forecast of the maximum hail size, given the biases in the hail mass budget equations and the parameterization of particle size distribution, with single-moment rimed ice species of the AAT scheme.
Significance Statement
Improving hail-forecasting skill, including the size, severity, and the spatial and temporal coverage of hail fall, has become an important subject for numerical weather prediction models as the model resolution increases. The objective of this study is to investigate the fundamental differences in hail parameterizations of three bulk microphysics schemes that lead to differences in the prediction of severe hail events and the spatial coverage of hail fall, hopefully providing insights into hail prediction with a regional numerical weather prediction model in the future.
Abstract
This analysis introduces a novel airborne Doppler radar database, referred to as the Tropical Cyclone Radar Archive of Doppler Analyses with Re-centering (TC-RADAR). TC-RADAR comprises over 900 analyses from 273 flights into TCs in the North Atlantic, eastern North Pacific, and central North Pacific basins between 1997 and 2020. This database contains abundant sampling across a wide range of TC intensities, which facilitated a comprehensive observational analysis on how the three-dimensional, kinematic TC inner-core structure is related to TC intensity. To examine the storm-relative TC structure, we implemented a novel TC center-finding algorithm. Here, we show that TCs below hurricane intensity tend to have monopolar radial profiles of vorticity and a wide range of vortex tilt magnitudes. As TC intensity increases, vorticity becomes maximized within an annulus inward of the peak wind, the vortex decays more slowly with height, and the vortex tends to be more aligned in the vertical. The TC secondary circulation is also strongly linked to TC intensity, as more intense storms have shallower and stronger lower-tropospheric inflow as well as larger azimuthally averaged ascent. The distribution of vertical velocity is found to vary with TC intensity, height, and radial domain. These results—and the capabilities of TC-RADAR—motivate multiple avenues for future work, which are discussed.
Significance Statement
Acquiring observations of the inner core of tropical cyclones (TCs) is a challenge due to the hazardous conditions inherent to the storm. A proven method of sampling the TC core region is the use of airborne radar. This study presents a novel database comprising over 900 airborne radar analyses collected in storms between 1997 and 2020, which is freely available to the research community. Here we demonstrate the utility of the database by examining how the three-dimensional structure of the TC core region changes depending upon the intensity of the storm. By identifying how the baseline TC vortex structure varies with TC intensity, this work provides the foundation for multiple future research avenues and model evaluation efforts.
Abstract
This analysis introduces a novel airborne Doppler radar database, referred to as the Tropical Cyclone Radar Archive of Doppler Analyses with Re-centering (TC-RADAR). TC-RADAR comprises over 900 analyses from 273 flights into TCs in the North Atlantic, eastern North Pacific, and central North Pacific basins between 1997 and 2020. This database contains abundant sampling across a wide range of TC intensities, which facilitated a comprehensive observational analysis on how the three-dimensional, kinematic TC inner-core structure is related to TC intensity. To examine the storm-relative TC structure, we implemented a novel TC center-finding algorithm. Here, we show that TCs below hurricane intensity tend to have monopolar radial profiles of vorticity and a wide range of vortex tilt magnitudes. As TC intensity increases, vorticity becomes maximized within an annulus inward of the peak wind, the vortex decays more slowly with height, and the vortex tends to be more aligned in the vertical. The TC secondary circulation is also strongly linked to TC intensity, as more intense storms have shallower and stronger lower-tropospheric inflow as well as larger azimuthally averaged ascent. The distribution of vertical velocity is found to vary with TC intensity, height, and radial domain. These results—and the capabilities of TC-RADAR—motivate multiple avenues for future work, which are discussed.
Significance Statement
Acquiring observations of the inner core of tropical cyclones (TCs) is a challenge due to the hazardous conditions inherent to the storm. A proven method of sampling the TC core region is the use of airborne radar. This study presents a novel database comprising over 900 airborne radar analyses collected in storms between 1997 and 2020, which is freely available to the research community. Here we demonstrate the utility of the database by examining how the three-dimensional structure of the TC core region changes depending upon the intensity of the storm. By identifying how the baseline TC vortex structure varies with TC intensity, this work provides the foundation for multiple future research avenues and model evaluation efforts.
Abstract
Modern general circulation models continue to require parameterizations of subgrid transport due to planetary boundary layer (PBL) turbulence and convection. Some schemes that unify these processes rely on assumed joint probability distributions of vertical velocity and moist conserved thermodynamic variables to predict the subgrid-scale contribution to the mean state of the atmosphere. The multivariate double-Gaussian mixture has been proposed as an appropriate model for PBL turbulence and shallow convection, but it is unable to reproduce important features of shallow cumulus convection. In this study, a novel unified PBL turbulence–convection–cloud macrophysics scheme is presented based on the eddy-diffusivity/mass-flux framework. The new scheme augments the double-Gaussian representation of subgrid variability with multiple stochastic mass-flux plumes at minimal added computational cost. Improved results for steady-state maritime and transient continental shallow convection from a single-column model implementation of the new scheme are shown with respect to reference large-eddy simulations. Improvements are seen in the cloud layer due to mass-flux plumes occupying the extreme moist, low liquid-water potential temperature tail of the joint temperature–moisture distribution.
Significance Statement
Computer models of the atmosphere used to predict future climate are unable to directly represent air motion at small spatial scales because it would take too long to run the model over the entire planet. Instead, models typically use coarse model grid spacing and a simplified statistical representation of the physical processes that cause small-scale motions. This paper improves a particular simplified representation by adding a mechanism to represent statistically rare events of strong small-scale air motion that coherently transport air from near the surface to higher in the atmosphere. This increased transport also improves the representation of clouds, a particularly difficult phenomenon to simulate in models.
Abstract
Modern general circulation models continue to require parameterizations of subgrid transport due to planetary boundary layer (PBL) turbulence and convection. Some schemes that unify these processes rely on assumed joint probability distributions of vertical velocity and moist conserved thermodynamic variables to predict the subgrid-scale contribution to the mean state of the atmosphere. The multivariate double-Gaussian mixture has been proposed as an appropriate model for PBL turbulence and shallow convection, but it is unable to reproduce important features of shallow cumulus convection. In this study, a novel unified PBL turbulence–convection–cloud macrophysics scheme is presented based on the eddy-diffusivity/mass-flux framework. The new scheme augments the double-Gaussian representation of subgrid variability with multiple stochastic mass-flux plumes at minimal added computational cost. Improved results for steady-state maritime and transient continental shallow convection from a single-column model implementation of the new scheme are shown with respect to reference large-eddy simulations. Improvements are seen in the cloud layer due to mass-flux plumes occupying the extreme moist, low liquid-water potential temperature tail of the joint temperature–moisture distribution.
Significance Statement
Computer models of the atmosphere used to predict future climate are unable to directly represent air motion at small spatial scales because it would take too long to run the model over the entire planet. Instead, models typically use coarse model grid spacing and a simplified statistical representation of the physical processes that cause small-scale motions. This paper improves a particular simplified representation by adding a mechanism to represent statistically rare events of strong small-scale air motion that coherently transport air from near the surface to higher in the atmosphere. This increased transport also improves the representation of clouds, a particularly difficult phenomenon to simulate in models.
Abstract
To help inform physics configuration decisions and help design and optimize a multi-physics Rapid Refresh Forecasting System (RRFS) ensemble to be used operationally by the National Weather Service, five FV3-LAM-based convection allowing forecasts were run on 35 cases between October 2020 and March 2021. These forecasts used ∼3-km grid spacing on a CONUS domain with physics configurations including Thompson, NSSL, and Ferrier–Aligo microphysics schemes, Noah, RUC, and NoahMP land surface models, and MYNN-EDMF, K-EDMF, and TKE-EDMF PBL schemes. All forecasts were initialized from the 0000 UTC GFS analysis and run for 84 h. Also, a subset of 8 cases were run with 15 combinations of physics options, also including the Morrison–Gettelman microphysics and Shin–Hong PBL schemes, to help attribute behaviors to individual schemes and isolate the main contributors of forecast errors. Evaluations of both sets of forecasts find that the CONUS-wide 24-h precipitation > 1 mm is positively biased across all five forecasts. NSSL microphysics displays a low bias in QPF along the Gulf Coast. Analyses show that it produces smaller raindrops prone to evaporation. Additionally, TKE-EDMF PBL in combination with Thompson microphysics displays a positive bias in precipitation over the Great Lakes and in the ocean near Florida due to higher latent heat fluxes calculated over water. Furthermore, the K-EDMF PBL scheme produces temperature errors that result in a negative bias in snowfall over the southern Mountain West. Finally, recommendations for which physics schemes to use in future suites and the RRFS ensemble are discussed.
Abstract
To help inform physics configuration decisions and help design and optimize a multi-physics Rapid Refresh Forecasting System (RRFS) ensemble to be used operationally by the National Weather Service, five FV3-LAM-based convection allowing forecasts were run on 35 cases between October 2020 and March 2021. These forecasts used ∼3-km grid spacing on a CONUS domain with physics configurations including Thompson, NSSL, and Ferrier–Aligo microphysics schemes, Noah, RUC, and NoahMP land surface models, and MYNN-EDMF, K-EDMF, and TKE-EDMF PBL schemes. All forecasts were initialized from the 0000 UTC GFS analysis and run for 84 h. Also, a subset of 8 cases were run with 15 combinations of physics options, also including the Morrison–Gettelman microphysics and Shin–Hong PBL schemes, to help attribute behaviors to individual schemes and isolate the main contributors of forecast errors. Evaluations of both sets of forecasts find that the CONUS-wide 24-h precipitation > 1 mm is positively biased across all five forecasts. NSSL microphysics displays a low bias in QPF along the Gulf Coast. Analyses show that it produces smaller raindrops prone to evaporation. Additionally, TKE-EDMF PBL in combination with Thompson microphysics displays a positive bias in precipitation over the Great Lakes and in the ocean near Florida due to higher latent heat fluxes calculated over water. Furthermore, the K-EDMF PBL scheme produces temperature errors that result in a negative bias in snowfall over the southern Mountain West. Finally, recommendations for which physics schemes to use in future suites and the RRFS ensemble are discussed.
Abstract
Four-dimensional variational (4D-Var) data assimilation (DA) is developed for a coupled atmosphere–ocean quasigeostrophic application. Complications arise in coupled data assimilation (CDA) systems due to the presence of multiple spatiotemporal scales. Various formulations of the background error covariance matrix (
Abstract
Four-dimensional variational (4D-Var) data assimilation (DA) is developed for a coupled atmosphere–ocean quasigeostrophic application. Complications arise in coupled data assimilation (CDA) systems due to the presence of multiple spatiotemporal scales. Various formulations of the background error covariance matrix (
Abstract
The transition process from laminar stratified shear layer to fully developed turbulence is usually captured using direct numerical simulations, in which the computational cost is extremely high and the numerical domain size is limited. In this work, we introduce a scale-aware subgrid-scale (SGS) parameterization, based on the gradient tensor of resolved variables, which is implemented in the Weather Research and Forecasting (WRF) Model. With this new SGS model, we can skillfully resolve the characteristics of transition process, including formation of vortex cores, merging vorticity billows, breaking waves into smaller scales, and developing secondary instability in the stratified shear layer even at coarse-resolution simulations. Our new model is developed such that the time scales of the eddy viscosity and diffusivity terms are represented using the tensor of the gradient and not that of the rate-of-strain, which is commonly used in the parameterization of turbulent-viscosity models. We show that time scales of unresolved transition processes in our new model are correlated with those of vorticity fields. At early times, the power-law slopes in the kinetic and available potential energy spectra are consistent with the process of formation and merging waves with an upscale energy transfer. At later times, the power-law slopes are in line with the process of breaking waves into small-scale motions with a downscale transfer. More importantly, the efficiency of turbulent mixing is mainly high at the edge of vortex filaments and not at the vortices’ eyes. These findings can improve our understanding of turbulent mixing process in large-scale wind-induced events, such as tropical cyclones, using the WRF Model.
Significance Statement
The evolution of instabilities in stratified shear layers has significant impacts on the structure of large-scale geophysical flows and also on the energy pathway to smaller-scale motions in internal waves and turbulence. Resolving transition processes in stratified shear layers requires very high-resolution simulations in climate models. We propose a new subgrid-scale parameterization that is implemented in the Weather Research and Forecasting Model to capture the dynamics of transition process from laminar to three-dimensional turbulence in stratified shear layers at coarse-resolution simulations. Our new scale-aware parameterization can reduce biases in climate models by skillfully representing unresolved fluxes, leading to higher accuracy in weather predictions of temperature, precipitation, and surface fluxes with an affordable computational cost.
Abstract
The transition process from laminar stratified shear layer to fully developed turbulence is usually captured using direct numerical simulations, in which the computational cost is extremely high and the numerical domain size is limited. In this work, we introduce a scale-aware subgrid-scale (SGS) parameterization, based on the gradient tensor of resolved variables, which is implemented in the Weather Research and Forecasting (WRF) Model. With this new SGS model, we can skillfully resolve the characteristics of transition process, including formation of vortex cores, merging vorticity billows, breaking waves into smaller scales, and developing secondary instability in the stratified shear layer even at coarse-resolution simulations. Our new model is developed such that the time scales of the eddy viscosity and diffusivity terms are represented using the tensor of the gradient and not that of the rate-of-strain, which is commonly used in the parameterization of turbulent-viscosity models. We show that time scales of unresolved transition processes in our new model are correlated with those of vorticity fields. At early times, the power-law slopes in the kinetic and available potential energy spectra are consistent with the process of formation and merging waves with an upscale energy transfer. At later times, the power-law slopes are in line with the process of breaking waves into small-scale motions with a downscale transfer. More importantly, the efficiency of turbulent mixing is mainly high at the edge of vortex filaments and not at the vortices’ eyes. These findings can improve our understanding of turbulent mixing process in large-scale wind-induced events, such as tropical cyclones, using the WRF Model.
Significance Statement
The evolution of instabilities in stratified shear layers has significant impacts on the structure of large-scale geophysical flows and also on the energy pathway to smaller-scale motions in internal waves and turbulence. Resolving transition processes in stratified shear layers requires very high-resolution simulations in climate models. We propose a new subgrid-scale parameterization that is implemented in the Weather Research and Forecasting Model to capture the dynamics of transition process from laminar to three-dimensional turbulence in stratified shear layers at coarse-resolution simulations. Our new scale-aware parameterization can reduce biases in climate models by skillfully representing unresolved fluxes, leading to higher accuracy in weather predictions of temperature, precipitation, and surface fluxes with an affordable computational cost.
