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Brian R. Greene
and
Scott T. Salesky

Abstract

For decades, stable boundary layer (SBL) turbulence has proven challenging to measure, parameterize, simulate, and interpret. Uncrewed aircraft systems (UAS) are becoming a reliable method to sample the atmospheric boundary layer, offering new perspectives for understanding the SBL. Moreover, continual computational advances have enabled the use of large-eddy simulations (LES) to simulate the atmosphere at ever-smaller scales. LES is therefore a powerful tool in establishing a baseline framework to understand the extent to which vertical profiles from UAS can represent larger-scale SBL flows. To quantify the representativeness of observations from UAS profiles and eddy-covariance observations within the SBL, we performed a random error analysis using a suite of six large-eddy simulations for a wide range of stabilities. We combine these random error estimates with emulated observations of a UAS and eddy-covariance systems to better inform future observational studies. For each experiment, we estimate relative random errors using the so-called relaxed filtering method for first- and second-order moments as functions of height and averaging time. We show that the random errors can be on the same order of magnitude as other instrument-based errors due to bias or dynamic response. Unlike instrument errors, however, random errors decrease with averaging time. For these reasons, we recommend coupling UAS observations with other ground-based instruments as well as dynamically adjusting the UAS vertical ascent rate to account for how errors change with height and stability.

Significance Statement

Weather-sensing uncrewed aircraft systems are rapidly being realized as effective tools to collect valuable observations within the atmospheric boundary layer. To fully capitalize on this novel observational technique, it is necessary to develop an understanding of how well their observations can represent the surrounding atmosphere across various spatial and temporal scales. In this study we quantify the representativeness of atmospheric observations in the stable boundary layer by evaluating the random errors for parameters such as temperature, wind speed, and fluxes as estimated from a suite of large-eddy simulations. Our results can better inform future studies utilizing uncrewed aircraft systems by highlighting how random errors in their observations relate to vertical ascent rate, atmospheric stability, and measurement height.

Restricted access
David J. Lorenz

Abstract

Changes in the latitude of the zonal-mean midlatitude jet play an important role for both natural variability and the response of the atmospheric circulation to greenhouse gases and other external forcing. Nevertheless, the jet response to external forcing exhibits perplexing and nonintuitive behavior. For example, external forcing that acts to strengthen the jet will also shift the jet poleward. In addition, for internal jet variability, zonal wind anomalies slowly propagate poleward over most latitudes; however, this propagation stalls somewhat at latitudes on the flanks of the mean jet. At these latitudes zonal wind anomalies are more stationary, and therefore, anomaly persistence is maximized. These same persistent latitudes are collocated with the zonal wind anomalies associated with the annular mode. Feedbacks between the zonal-mean zonal wind and the eddy momentum fluxes are responsible for the above behaviors. Here a simple mechanistic model of the effect of the zonal-mean zonal wind on the eddy momentum fluxes is developed. The model reproduces the wave–mean flow feedbacks that maintain the annular mode, cause stronger jets to shift poleward (and vice versa), and cause the poleward propagation of zonal wind anomalies. In the model, the effect of the mean flow on the eddy momentum fluxes is determined solely by the critical level and the reflecting level. The model is used to distill the essential dynamics of annular variability and change such as why stronger jets shift poleward, why high-frequency eddies are responsible for the positive feedback and why the intricate structure of propagating versus stationary zonal wind anomalies exists.

Restricted access
Yuan Lian
,
Mark I. Richardson
,
Claire E. Newman
,
Chris Lee
,
Anthony Toigo
,
Scott Guzewich
, and
Roger V. Yelle

Abstract

Atmospheric oscillations with daily periodicity are observed in in situ near-surface pressure, temperature, and winds observations and also in remotely sensed temperature and pressure observations of the Martian atmosphere. Such oscillations are interpreted as thermal tides driven by the diurnal cycle of solar radiation and occur at various frequencies, with the most prominent being the diurnal, semidiurnal, terdiurnal, and quadiurnal tides. Mars global circulation models reproduce these tides with varying levels of success. Until recently, both the MarsWRF and newly developed MarsMPAS models were able to produce realistic diurnal and semidiurnal tide amplitudes but predicted higher-order mode amplitudes that were significantly weaker than observed. We use linear wave analysis to show that the divergence damping applied within both MarsWRF and MarsMPAS is responsible for suppressing the amplitude of thermal tides with frequency greater than 2 per sol, despite being designed to suppress only acoustic wave modes. Decreasing the strength of the divergence damping in MarsWRF and MarsMPAS allows for excellent prediction of the higher-order tidal modes. This finding demonstrates that care must be taken when applying numerical dampers and filters that may eliminate some desired dynamical features in planetary atmospheres.

Open access
Justin Finkel
,
Robert J. Webber
,
Edwin P. Gerber
,
Dorian S. Abbot
, and
Jonathan Weare

Abstract

Atmospheric regime transitions are highly impactful as drivers of extreme weather events, but pose two formidable modeling challenges: predicting the next event (weather forecasting) and characterizing the statistics of events of a given severity (the risk climatology). Each event has a different duration and spatial structure, making it hard to define an objective “average event.” We argue here that transition path theory (TPT), a stochastic process framework, is an appropriate tool for the task. We demonstrate TPT’s capacities on a wave–mean flow model of sudden stratospheric warmings (SSWs) developed by Holton and Mass, which is idealized enough for transparent TPT analysis but complex enough to demonstrate computational scalability. Whereas a recent article () studied near-term SSW predictability, the present article uses TPT to link predictability to long-term SSW frequency. This requires not only forecasting forward in time from an initial condition, but also backward in time to assess the probability of the initial conditions themselves. TPT enables one to condition the dynamics on the regime transition occurring, and thus visualize its physical drivers with a vector field called the reactive current. The reactive current shows that before an SSW, dissipation and stochastic forcing drive a slow decay of vortex strength at lower altitudes. The response of upper-level winds is late and sudden, occurring only after the transition is almost complete from a probabilistic point of view. This case study demonstrates that TPT quantities, visualized in a space of physically meaningful variables, can help one understand the dynamics of regime transitions.

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Gwenore F. Pokrifka
,
Alfred M. Moyle
, and
Jerry Y. Harrington

Abstract

An electrodynamic levitation thermal-gradient diffusion chamber was used to grow 268 individual, small ice particles (initial radii of 8–26 μm) from the vapor, at temperatures ranging from −65° to −40°C, and supersaturations up to liquid saturation. Growth limited by attachment kinetics was frequently measured at low supersaturation, as shown in prior work. At high supersaturation, enhanced growth was measured, likely due to the development of branches and hollowed facets. The effects of branching and hollowing on particle growth are often treated with an effective density ρ eff. We fit the measured time series with two different models to estimate size-dependent ρ eff values: the first model decreases ρ eff to an asymptotic deposition density ρ dep, and the second models ρ eff by a power law with exponent P. Both methods produce similar results, though the fits with ρ dep typically have lower relative errors. The fit results do not correspond well with models of isometric or planar single-crystalline growth. While single-crystalline columnar crystals correspond to some of the highest growth rates, a newly constructed geometric model of budding rosette crystals produces the best match with the growth data. The relative frequency of occurrence of ρ dep and P values show a clear dependence on ice supersaturation normalized to liquid saturation. We use these relative frequencies of ρ dep and P to derive two supersaturation-dependent mass–size relationships suitable for cloud modeling applications.

Restricted access
Ji-Hee Yoo
and
Hye-Yeong Chun

Abstract

Compensation between the resolved wave (RW) forcing and the parameterized orographic gravity wave drag (OGWD) accompanying barotropic/baroclinic (BT/BC) instability in the realistic atmosphere is investigated using Climate Forecast System Reanalysis data in the Northern Hemisphere winter stratosphere. When sufficiently narrow and/or strong negative OGWD drives instability, RWs are generated in situ, providing positive Eliassen–Palm flux divergence that compensates for the parameterized OGWD enhancement; this is consistent with the findings of previous studies based on the idealized general circulation models. However, dependence of the compensation rate on RW forcing differs from the nearly complete compensation in the previous studies, implying that an additional mechanism operates for the compensation: the refractive-index modification by BT/BC instability. The negative meridional gradient of the quasigeostrophic potential vorticity leads to the negative refractive index squared for RWs with phase speeds less than the zonal-mean zonal wind. This prevents RWs from entering the destabilized areas, resulting in the divergence of Eliassen–Palm fluxes that cancels out the parameterized OGWD perturbation. Although both mechanisms act simultaneously, the refractive-index modification plays an important role in the compensation processes in the stratosphere where RWs are dominated by the planetary-scale waves.

Open access
Mark Pinsky
and
Alexander Khain

Abstract

Velocity field in a nonprecipitating Cu under BOMEX conditions, simulated by SAM with 10-m resolution and spectral bin microphysics is separated into the convective part and the turbulent part, using a wavelet filtering. In Part II of the study properties of convective motions of this Cu were investigated. Here in Part III of the study, the parameters of cloud turbulence are calculated in the cloud updraft zone at different stages of cloud development. The main points of this study are (i) application of a fine-scale LES model of a single convective cloud allowed a direct estimation of turbulence parameters using the resolved flow in the cloud and (ii) the separation of the resolved flow into the turbulence flow and the nonturbulence flow allowed us to estimate different turbulent parameters with sufficient statistical accuracy. We calculated height and time dependences of the main turbulent parameters such as turbulence kinetic energy (TKE), spectra of TKE, dissipation rate, and the turbulent coefficient. It was found that the main source of turbulence in the cloud is buoyancy whose contribution is described by the buoyancy production term (BPT). The shear production term (SPT) increases with height and reaches its maximum near cloud top, and so does BPT. In agreement with the behavior of BPT and SPT, turbulence in the lower cloud part (below the inversion level) is weak and hardly affects the processes of mixing and entrainment. The fact that BPT is larger than SPT determines many properties of cloud turbulence. For instance, the turbulence is nonisotropic, so the vertical component of TKE is substantially larger than the horizontal components. Another consequence of the fact that BPT is larger than STP manifests itself in the finding that the turbulence spectrum largely obeys the −11/5 Bolgiano–Obukhov scaling. The classical Kolmogorov −5/3 scaling dominates for the low part of a cloud largely at the dissolving stage of cloud evolution. Using the spectra obtained we evaluated an “effective” dissipation rate which increases with height from nearly zero at cloud base up to 20 cm2 s−3 near cloud top. The coefficient of turbulent diffusion was found to increase with height and ranged from 5 m2 s−1 near cloud base to 25 m2 s−1 near cloud top. The possible role of turbulence in the process of lateral entrainment and mixing is discussed.

Significance Statement

1) This study investigates the turbulent structure of Cu using a 10-m-resolution LES model with spectral bin microphysics, 2) the main source of turbulence is buoyancy, 3) turbulence in cumulus clouds (Cu) is nonisotropic, 4) turbulence reaches maximum intensity near cloud top, 5) turbulence spectrum obeys largely the −11/5 Bolgiano–Obukhov scaling, and 6) the main turbulent parameters are evaluated.

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Inna Polichtchouk
,
Annelize van Niekerk
, and
Nils Wedi

Abstract

Global ECMWF IFS simulations with horizontal grid spacings of 1, 4, and 9 km are used to assess gravity wave forcing (GWF) in the extratropical stratosphere. Results with important implications for GWF parameterizations at high and intermediate resolutions are presented. A doubling in the zonal-mean resolved GWF is observed when the horizontal resolution is increased from 9 to 1 km. Small-scale gravity waves with horizontal wavelengths < 100 km dominate this increase. Over most regions, excluding the polar night jet in the Antarctic spring, the total (resolved + parameterized) GWF at 9 km (4 km) is underestimated by up to 30% (15%). This implies that the parameterization of GWF is still required at 9 and 4 km horizontal resolutions. Despite the small land area in the Southern Hemisphere (SH), the resolved orographic and nonorographic GWF contribute equally to the total GWF in the SH at 1 km resolution. This is not reflected in the partitioning of the parameterized GWF, which has a significantly larger nonorographic contribution at 9 km. As a result, a zonal-mean momentum budget analysis reveals that the total GWF contributes one-third of SH springtime polar vortex deceleration at 1 km, whereas the contribution is as much as 50% at 9 km. This suggests that a rebalancing of the parameterized nonorographic and orographic GWF is required.

Restricted access
Difei Deng
and
Elizabeth A. Ritchie

Abstract

Tropical Cyclone Debbie (2017) made landfall near Airlie Beach on 28 March 2017 causing 14 fatalities and an estimated $2.67 billion (U.S. dollars) economic loss and was ranked as the most dangerous cyclone to hit Australia since TC Tracy in 1974. In addition to the extreme flooding as TC Debbie moved onshore and down the east coast of Australia, it intensified rapidly just offshore from category 2 to category 4 on the Australian TC intensity scale in under 18 h prior to making landfall. A high-resolution WRF simulation is used to analyze the inner-core structure and evolution during the offshore intensification period. Two stages are identified: a slow intensification (SI) stage characterized by an asymmetric eyewall contraction and a rapid intensification (RI) stage characterized by three eyewall breakdown and redevelopment events. Each round of breakdown and reestablishment brings high potential vorticity and equivalent potential temperature air back into the eyewall, reinvigorating eyewall convection activity and driving intensification.

Open access
Mozhgan Amiramjadi
,
Riwal Plougonven
,
Ali R. Mohebalhojeh
, and
Mohammad Mirzaei

Abstract

Machine learning (ML) provides a powerful tool for investigating the relationship between the large-scale flow and unresolved processes, which need to be parameterized in climate models. The current work explores the performance of the random forest regressor (RF) as a nonparametric model in the reconstruction of nonorographic gravity waves (GWs) over midlatitude oceanic areas. The ERA5 dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF) model outputs is employed in its full resolution to derive GW variations in the lower stratosphere. Coarse-grained variables in a column-based configuration of the atmosphere are used to reconstruct the GWs variability at the target level. The first important outcome is the relative success in reconstructing the GW signal (coefficient of determination R 2 ≈ 0.85 for “E3” combination). The second outcome is that the most informative explanatory variable is the local background wind speed. This questions the traditional framework of gravity wave parameterizations, for which, at these heights, one would expect more sensitivity to sources below than to local flow. Finally, to test the efficiency of a relatively simple, parametric statistical model, the efficiency of linear regression was compared to that of random forests with a restricted set of only five explanatory variables. Results were poor. Increasing the number of input variables to 15 hardly changes the performance of the linear regression (R 2 changes slightly from 0.18 to 0.21), while it leads to better results with the random forests (R 2 increases from 0.29 to 0.37).

Open access