Abstract

A companion paper by Fritts et al. (2023a) reviews evidence for Kelvin-Helmholtz instability (KHI) “tube” and “knot” (T&K) dynamics that appear to be widespread throughout the atmosphere. Here we describe the results of an idealized direct numerical simulation of multi-scale gravity wave dynamics that reveals multiple larger- and smaller-scale KHI T&K events. The results enable assessments of the environments in which these dynamics arise and their competition with concurrent gravity wave breaking in driving turbulence and energy dissipation. A larger-scale event is diagnosed in detail and reveals diverse and intense T&K dynamics driving more intense turbulence than occurs due to gravity wave breaking in the same environment. Smaller-scale events reveal that KHI T&K dynamics readily extend to weaker, smaller-scale, and increasingly viscous shear flows. Our results suggest that KHI T&K dynamics should be widespread, perhaps ubiquitous, wherever superposed gravity waves induce intensifying shear layers, because such layers are virtually always present. A second companion paper (Fritts et al. 2023b) demonstrates that KHI T&K dynamics exhibit elevated turbulence generation and energy dissipation rates extending to smaller Reynolds numbers for relevant KHI scales wherever they arise. These dynamics are suggested to be significant sources of turbulence and mixing throughout the atmosphere that are currently ignored or under-represented in turbulence parameterizations in regional and global models.

Abstract

A scale-dependent dynamic Smagorinsky model is implemented in the Met Office/NERC Cloud (MONC) model using two averaging flavors, along Lagrangian pathlines and local moving averages. The dynamic approaches were compared against the conventional Smagorinsky–Lilly scheme in simulating the diurnal cycle of shallow cumulus convection. The simulations spanned from the LES to the near-gray-zone and gray-zone resolutions and revealed the adaptability of the dynamic model across the scales and different stability regimes. The dynamic model can produce a scale- and stability-dependent profile of the subfilter turbulence length scale across the chosen resolution range. At gray-zone resolutions the adaptive length scales can better represent the early precloud boundary layer leading to temperature and moisture profiles closer to the LES compared to the standard Smagorinsky. As a result, the initialization and general representation of the cloud field in the dynamic model is in good agreement with the LES. In contrast, the standard Smagorinsky produces a less well-mixed boundary layer, which fails to ventilate moisture from the boundary layer, resulting in the delayed spinup of the cloud layer. Moreover, strong downgradient diffusion controls the turbulent transport of scalars in the cloud layer. However, the dynamic approaches rely on the resolved field to account for nonlocal transports, leading to overenergetic structures when the boundary layer is fully developed and the Lagrangian model is used. Introducing the local averaging version of the model or adopting a new Lagrangian time scale provides stronger dissipation without significantly affecting model behavior.

Abstract

The influence of the surface latent and surface sensible heat flux on the development and interaction of an idealized extratropical cyclone (termed “primary”) with an upstream cyclone (termed “upstream”) using the Navy’s Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) is analyzed. The primary cyclone develops from an initial perturbation to a baroclinically unstable jet stream, while the upstream cyclone results from Rossby wave dispersion at the surface where a bottom-up style development occurs. The intensity of the upstream cyclone is strongly enhanced by surface latent heat fluxes and, to a lesser degree, by surface sensible heat fluxes. Forward trajectories initiated from the postfrontal sector of the primary cyclone travel south of the upstream anticyclone and feed into the atmospheric river and warm conveyor belt region of the upstream cyclone. Substantial moistening of this airstream is a result of upward surface latent heat flux present in both the primary cyclone’s postfrontal sector and along the southern flank of the anticyclone. Backward trajectories initiated from the same region show that these air parcels originate from a broad area north of both the anticyclone and the primary cyclone in the lower troposphere. The airstream identified represents a new pathway through which dry, descending air that is preconditioned through surface moistening enhances the development of an upstream cyclone through diabatically generated potential vorticity.

Abstract

Much of our conceptual understanding of midlatitude atmospheric motion comes from two-layer quasigeostrophic (QG) models. Traditionally, these QG models do not include moisture, which accounts for an estimated 30%–60% of the available energy of the atmosphere. The atmospheric moisture content is expected to increase under global warming, and therefore, a theory for how moisture modifies atmospheric dynamics is crucial. We use a two-layer moist QG model with convective adjustment as a basis for analyzing how latent heat release and large-scale moisture gradients impact the scalings of a midlatitude system at the synoptic scale. In this model, the degree of saturation can be tuned independently of other moist parameters by enforcing a high rate of evaporation from the surface. This allows for study of the effects of latent heat release at saturation, without the intrinsic nonlinearity of precipitation. At saturation, this system is equivalent to the dry QG model under a rescaling of both length and time. This predicts that the most unstable mode shifts to smaller scales, the growth rates increase, and the inverse cascade extends to larger scales. We verify these results numerically and use them to verify a framework for the complete energetics of a moist system. We examine the spectral features of the energy transfer terms. This analysis shows that precipitation generates energy at small scales, while dry dynamics drive a significant broadening to larger scales. Cascades of energy are still observed in all terms, albeit without a clearly defined inertial range.

Abstract

A novel high-resolution regional reanalysis is used to investigate the mesoscale processes that preceded the formation of Tropical Cyclone (TC) Mora (2017). Both satellite observations and the regional reanalysis show early morning mesoscale convective systems (MCSs) persistently initiated and organized in the downshear quadrant of the preexisting tropical disturbance a few days prior to the genesis of TC Mora. The diurnal MCSs gradually enhanced the meso-α-scale vortex near the center of the preexisting tropical disturbance through vortex stretching, providing a vorticity-rich and moist environment for the following burst of deep convection and enhancement of the meso-β-scale vortex. The regional reanalysis shows that the gravity waves that radiated from afternoon convection over the northern coast of the Bay of Bengal might play an important role in modulating the diurnal cycle of pregenesis MCSs. The diurnal convectively forced gravity waves increased the tropospheric stability, reduced the column saturation fraction, and suppressed deep convection within the preexisting tropical disturbance from noon to evening. A similar quasi-diurnal cycle of organized deep convection prior to TC genesis has also been observed over other basins. However, modeling studies are needed to conclusively demonstrate the relationships between the gravity waves and pregenesis diurnal MCSs. Also, whether diurnal gravity waves play a similar role in modulating the pregenesis deep convection in other TCs is worth future investigations.

Abstract

Convective variability is used to diagnose different pathways towards convective self-aggregation (CSA) in radiative-convective equilibrium simulations with two cloud-resolving models, SCALE and VVM. The results show that convection undergoes gradual growth in SCALE and fast transition in VVM, which is associated with different mechanisms between the two models. In SCALE, strong radiative cooling associated with a dry environment drives the circulation from the dry region, and the dry environment results from strong subsidence and insufficient surface flux supply. The circulation driven by the radiative cooling then pushes convection aggregating, which is the dry-radiation pathway. In VVM, CSA develops due to the rapid strengthening of circulation driven by convective systems in the moist region, which is the convection-upscaling pathway. The different pathways of CSA development can be attributed to the upscale process of convective structures identified by the cloud size spectrum. The upscaling of large-size convective systems can enhance circulation from the moist region in VVM. In SCALE, the infrequent appearance of large convective systems is insufficient to generate circulation, as compensating subsidence can occur within the moist region even in the absence of convective systems. This study shows that the convective variabilities between models can lead to different pathways of CSA, and mechanism-denial experiments also support our analyses.

Abstract

This study investigates whether quasi-random surface vertical vorticity is sufficient for tornadogenesis when combined with an updraft typical of tornadic supercells. The viability of this pathway could mean that a coherent process to produce well-organized surface vertical vorticity is rather unimportant. Highly idealized simulations are used to establish random noise as a possible seed for the production of tornado-like vortices (TLVs). A number of sensitivities are then examined across the simulations. The most explanatory predictor of whether a TLV will form (and how strong it will become) is the maximal value of initial surface circulation found near the updraft. Perhaps surprisingly, sufficient circulation for tornadogenesis is often present even when the surface vertical vorticity field lacks any obvious organized structure. The other key ingredient for TLV formation is confirmed to be a large vertical gradient in vertical velocity close to the ground (to promote stretching). Overall, it appears that random surface vertical vorticity is indeed sufficient for TLV formation given adequate stretching. However, it is shown that longer-wavelength noise is more likely to be associated with substantial surface circulation (because it is the areal integral of vertical vorticity). Thus, coherent vorticity sources that produce longer-wavelength structures are likely to be the most supportive of tornadogenesis.

Abstract

The hypothesis that predictability depends on the atmospheric state in the planetary-scale low-frequency variability in boreal winter was examined. We first computed six typical weather patterns from 500-hPa geopotential height anomalies in the Northern Hemisphere using self-organizing map (SOM) and k-clustering analysis. Next, using 11 models from the subseasonal-to-seasonal (S2S) operational and reforecast archive, we computed each model’s climatology as a function of lead time to evaluate model bias. Although the forecast bias depends on the model, it is consistently the largest when the forecast begins from the atmospheric state with a blocking-like pattern in the eastern North Pacific. Moreover, the ensemble-forecast spread based on S2S multimodel forecast data was compared with empirically estimated Fokker–Planck equation (FPE) parameters based on reanalysis data. The multimodel mean ensemble-forecast spread was correlated with the diffusion tensor norm; they are large for the cases when the atmospheric state started from a cluster with a blocking-like pattern. As the multimodel mean is expected to substantially reduce model biases and may approximate the predictability inherent in nature, we can summarize that the atmospheric state corresponding to the cluster was less predictable than others.

Abstract

The thermodynamic processes associated with convection in Tropical African and Northeastern Pacific Easterly Waves (AEWs and PEWs, respectively) are examined on the basis of Empirical Orthogonal Functions (EOFs) and a plume-buoyancy framework. Linear regression analysis reveals the relationship between temperature, moisture, buoyancy, and precipitation in EWs. Plume buoyancy is found to be highly correlated with rainfall in both AEWs and PEWs, and a near 1:1 relationship is found between a buoyancy-based diagnostic of rainfall and rainfall rates from ERA5. Close inspection of the contribution of moisture and temperature to plume buoyancy reveals that temperature and moisture contribute roughly equally to the buoyancy in AEWs, while moisture dominates the distribution of buoyancy in PEWs. A scale analysis is performed in order to understand the relative amplitudes of temperature and moisture in easterly waves. It is found that the smaller contribution of temperature to the thermodynamics of PEWs relative to AEWs is related to their slower propagation speed, which allows PEWs to more robustly adjust to weak temperature gradient (WTG) balance. The consistency of the buoyancy analysis and the scale analysis indicates that PEWs are moisture modes: waves in which water vapor plays a dominant role in their thermodynamics. AEWs, on the other hand, are mixed waves in which temperature and moisture play similar roles in their thermodynamics.

Abstract

Predicting the rapid intensification (> 15.0 m s⁻¹ increase in 10m wind speed over 24 hours or less) of tropical cyclones (TC) remains a challenge in the broader context of numerical weather prediction largely due to their multiscale dynamics. Ocean observations show that the size and magnitude of sea surface temperature (SST) anomalies associated with cold wakes and ocean eddies play important roles in TC dynamics.

In this study, a combination of spectral and structure function analyses is utilized to generate realistic realizations of multiscale anomalies characteristic of the SST conditions in which Hurricane Irma (2017) underwent rapid intensification (RI). We investigate the impact of the length scale of these SST anomalies and the role of translation speed on the variance in RI onset timing.

Length-scale-induced convective asymmetries, in addition to the mean magnitude of SST anomalies beneath the storm eye, are shown to modulate the variance in RI onset timing. The size of the associated SST length scales relative to the storm size is critical to the magnitude of variance in RI onset timing, as smaller length scales are shown to lack the spatial extent required to induce preferential convective asymmetries. Storm translation speed is also shown to influence the variance in RI onset timing for larger length scale ensembles by altering the exposure time of the eye to these SST anomalies. We find that an interplay between SST-induced convective asymmetries, the magnitude of SST anomalies underneath the eye/eye-wall, and storm translation speed play crucial roles in modulating the variance in RI onset timing.