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Lu Zhang
,
Hongsheng Zhang
,
Xuhui Cai
,
Yu Song
, and
Xiaoye Zhang

Abstract

The Taklimakan Desert is one of key climate regions in East Asia, both highly influencing and highly sensitive to local/regional climate change. Based on a comprehensive observation experiment from 1 to 31 May 2022 in the hinterland of the Taklimakan Desert, the characteristics and mechanisms of turbulence intermittency are investigated in this study, with the purpose to correct turbulent fluxes. Using an improved algorithm to decompose turbulence and submeso motions, two intermittency regimes are recognized in the Taklimakan Desert, namely, D and T intermittency and onD intermittency. The former occurs under strongly stable conditions, characterized by the coexistence of dynamic and thermodynamic turbulence intermittency. The latter occurs under strongly unstable conditions and represents only dynamic turbulence intermittency. Physically, the D and T intermittency regime is related to submeso waves, whereas the onD regime is caused by the horizontal convergence/divergence of convective circulations. With the influence of intermittency and submeso motions, the observed turbulent statistics deviate from reality, which would mask the similarity relationships. To overcome the problem, turbulent statistics are corrected by removing submeso components from original fluctuations. The effectiveness of this method is demonstrated based on the flux–gradient relationships. It is also suggested that, for a big dataset, the impact of onD intermittency can be simply corrected by a correction factor while that of D and T intermittency cannot. The results of this study are helpful to develop the parameterization of turbulent exchange processes in the Taklimakan Desert, which is significant to improve the accuracy of weather forecasting and climate prediction.

Significance Statement

The Taklimakan Desert plays an important role in the evolution of weather and climate in East Asia. With strong surface thermal forcing, turbulence often shows distinctive intermittency, which largely constrains the evaluation of land–atmosphere exchange in this key climate region. This study aims to understand the characteristics of turbulence intermittency and its physical mechanisms, and further to correct the influence of turbulence intermittency on turbulent fluxes in the Taklimakan Desert. This is significant because the results are helpful to improve the parameterization of subgrid processes in the key climate region for atmospheric models, which points the way toward enhancing the accuracy of weather forecasting and climate prediction.

Open access
Aaron Wang
,
Xiang I. A. Yang
, and
Mikhail Ovchinnikov

Abstract

The traditional approach of using the Monin–Obukhov similarity theory (MOST) to model near-surface processes in large-eddy simulations (LESs) can lead to significant errors in natural convection. In this study, we propose an alternative approach based on feedforward neural networks (FNNs) trained on output from direct numerical simulation (DNS). To evaluate the performance, we conduct both a priori and a posteriori tests. In the a priori (offline) tests, we compare the statistics of the surface shear stress and heat flux, computed from filtered DNS input variables, to the stress and flux obtained from the filtered DNS. Additionally, we investigate the importance of various input features using the Shapley additive explanations value and the conditional average of the filter grid cells. In the a posteriori (online) tests, we implement the trained models in the System for Atmospheric Modeling (SAM) LES and compare the LES-generated surface shear stress and heat flux with those in the DNS. Our findings reveal that vertical velocity, a traditionally overlooked flow quantity, is one of the most important input features for determining the wall fluxes. Increasing the number of input features improves the a priori test results but does not always improve the model performance in the a posteriori tests because of the differences in input variables between the LES and DNS. Last, we show that physics-aware FNN models trained with logarithmic and scaled parameters can well extrapolate to more intense convection scenarios than in the training dataset, whereas those trained with primitive flow quantities cannot.

Significance Statement

The traditional near-surface turbulence model, based on a shear-dominated boundary layer flow, does not represent near-surface turbulence in natural convection. Using a feedforward neural network (FNN), we can construct a more accurate model that better represents the near-surface turbulence in various flows and reveals previously overlooked controlling factors and process interactions. Our study shows that the FNN-generated models outperform the traditional model and highlight the importance of the near-surface vertical velocity. Furthermore, the physics-aware FNN models exhibit the potential to extrapolate to convective flows of various intensities beyond the range of the training dataset, suggesting their broader applicability for more accurate modeling of near-surface turbulence.

Open access
A. Possner
,
K. Pfannkuch
, and
V. Ramadoss

Abstract

Field measurements and modeling studies suggest that secondary ice production (SIP) may close the gap between observed Arctic ice nucleating particle (INP) concentrations and ice crystal number concentrations ni . Here, we explore sensitivities with respect to the complexity of different INP parameterizations under the premise that ni is governed by SIP. Idealized, cloud-resolving simulations are performed for the marine cold air outbreak cloud deck sampled during the Mixed-Phase Arctic Cloud Experiment (M-PACE) with the Icosahedral Nonhydrostatic (ICON) model. The impact of the droplet shattering (DS) of raindrops and collisional breakup (BR) in addition to the existing Hallet–Mossop rime splintering mechanism were investigated. Overall, 12 different model experiments (12-h runs) were performed and analyzed. Despite the considerable amount of uncertainty remaining with regard to SIP mechanisms and their process representation in numerical models, we conclude from these experiments that (i) only simulations where DS dominates the SIP signal (potentially amplified by BR) capture observed ice-phase and liquid-phase cloud properties, and (ii) SIP events cluster around the convective outflow region and are structurally linked to mesoscale cloud organization. In addition, interactions with primary nucleation parameterizations of varied complexity were investigated. Here, our simulations show that (i) a stable long-lived mixed-phase cloud (MPC) can be maintained in the absence of primary nucleation once SIP is established, (ii) experiments using a computationally more efficient relaxation-based parameterization of primary nucleation are statistically invariant from simulations considering prognostic INP, and (iii) primary nucleation at cloud-top controls the areal extent of the mixed-phase cloud region, and reduces SIP efficacy via DS due to increased depletion of cloud liquid throughout the entire cloud column.

Significance Statement

Secondary ice production (SIP) remains a key challenge in our understanding of boundary layer mixed-phase clouds. Here, we use sensitivity experiments performed with the ICON model at the cloud-resolving scale to explore potential interactions between primary nucleation, SIP, and mesoscale cloud organization. We simulate an Arctic single-layer cold air outbreak stratocumulus deck that was sampled during the M-PACE campaign. We find that once established, SIP alone is sufficient to maintain the mixed-phase cloud state until the end of the simulation. Our sensitivity analysis also shows that numerically more efficient treatments of immersion freezing are statistically invariant from simulations with a full prognostic INP budget.

Open access
Troy J. Zaremba
,
Robert M. Rauber
,
Kaylee Heimes
,
John E. Yorks
,
Joseph A. Finlon
,
Stephen D. Nicholls
,
Patrick Selmer
,
Lynn A. McMurdie
, and
Greg M. McFarquhar

Abstract

Cloud-top phase (CTP) impacts cloud albedo and pathways for ice particle nucleation, growth, and fallout within extratropical cyclones. This study uses airborne lidar, radar, and Rapid Refresh analysis data to characterize CTP within extratropical cyclones as a function of cloud-top temperature (CTT). During the 2020, 2022, and 2023 Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign deployments, the Earth Resources 2 (ER-2) aircraft flew 26 research flights over the northeast and midwest United States to sample the cloud tops of a variety of extratropical cyclones. A training dataset was developed to create probabilistic phase classifications based on Cloud Physics Lidar measurements of known ice and liquid clouds. These classifications were then used to quantify dominant CTP in the top 150 m of clouds sampled by the Cloud Physics Lidar in storms during IMPACTS. Case studies are presented illustrating examples of supercooled liquid water at cloud top at different CTT ranges (−3° < CTTs < −35°C) within extratropical cyclones. During IMPACTS, 19.2% of clouds had supercooled liquid water present at cloud top. Supercooled liquid was the dominant phase in extratropical cyclone cloud tops when CTTs were >−20°C. Liquid-bearing cloud tops were found at CTTs as cold as −37°C.

Significance Statement

Identifying supercooled liquid cloud tops’ frequency is crucial for understanding ice nucleation mechanisms at cloud top, cloud radiative effects, and aircraft icing. In this study, airborne lidar, radar, and model temperature data from 26 research flights during the NASA IMPACTS campaign are used to characterize extratropical cyclone cloud-top phase (CTP) as a function of cloud-top temperature (CTT). The results show that liquid was the dominant CTP present in extratropical cyclone cloud tops when CTTs were >−20°C with decreasing supercooled liquid cloud-top frequency at temperatures < −20°C. Nevertheless, liquid was present at CTTs as cold as −37°C.

Open access
Alessandro C. M. Savazzi
,
Louise Nuijens
,
Wim de Rooy
,
Martin Janssens
, and
A. Pier Siebesma

Abstract

This study investigates momentum transport in shallow cumulus clouds as simulated with the Dutch Atmospheric Large Eddy Simulation (DALES) for a 150 × 150 km2 domain east of Barbados during 9 days of EUREC4A. DALES is initialized and forced with the mesoscale weather model HARMONIE–AROME and subjectively reproduces observed cloud patterns. This study examines the evolution of momentum transport, which scales contribute to it, and how they modulate the trade winds. Daily-mean momentum flux profiles show downgradient zonal momentum transport in the subcloud layer, which turns countergradient in the cloud layer. The meridional momentum transport is nontrivial, with mostly downgradient transport throughout the trade wind layer except near the top of the surface layer and near cloud tops. Substantial spatial and temporal heterogeneity in momentum flux is observed with much stronger tendencies imposed in areas of organized convection. The study finds that while scales < 2 km dominate momentum flux at 200 m in unorganized fields, submesoscales O ( 2–2 0 ) km carry up to 50% of the zonal momentum flux in the cloud layer in organized fields. For the meridional momentum flux, this fraction is even larger near the surface and in the subcloud layer. The scale dependence of the momentum flux is not explained by changes in convective or boundary layer depth. Instead, the results suggest the importance of spatial heterogeneity, increasing horizontal length scales, and countergradient transport in the presence of organized convection.

Open access
Jun-Ichi Yano
and
Marta Wacławczyk

Abstract

The symmetries of the governing equations of atmospheric flows constrain the solutions. The present study applies those symmetries identified from the governing equations to the atmospheric boundary layers under relatively weak stratifications (stable and unstable). More specifically, the invariant solutions are analyzed, which conserve their forms under possible symmetry transformations of a governing equation system. The key question is whether those invariant solutions can rederive the known vertical profiles of both vertical fluxes and the means for the horizontal wind and the potential temperature. The mean profiles for the wind and the potential temperature in the surface layer predicted from the Monin–Obukhov theory can be recovered as invariant solutions. However, the consistent vertical fluxes both for the momentum and heat no longer remain constant with height, as assumed in the Monin–Obukhov theory, but linearly and parabolically change with height over the dynamic sublayer and the above, respectively, in stable conditions. The present study suggests that a deviation from the constancy, though observationally known to be weak, is a crucial part of the surface-layer dynamics to maintain its symmetry consistency.

Significance Statement

The atmospheric flows are governed by a differential equation system, which is often difficult to solve in any satisfactory manner, either analytically or numerically. However, without solving them explicitly, many insights can be obtained by examining the “symmetries” of the governing equations. The study suggests that basic vertical profiles of the mean state of the atmospheric boundary layer is more strongly constrained by the symmetry consistency than suggested by standard similarity theories.

Open access
Manuel Santos Gutiérrez
and
Kalli Furtado

Abstract

The supersaturation equation for a vertically moving adiabatic cloud parcel is analyzed. The effects of turbulent updrafts are incorporated in the shape of a stochastic Lagrangian model, with spatial and time correlations expressed in terms of turbulent kinetic energy. Using the Fokker–Planck equation, the steady-state probability distributions of supersaturation are analytically computed for a number of approximations involving the time-scale separation between updraft fluctuations and phase relaxation, and droplet or ice particle size fluctuations. While the analytical results are presented in general for single-phase clouds, the calculated distributions are used to compute mixed-phase cloud properties—mixed fraction and mean liquid water content in an initially icy cloud—and are argued to be useful for generalizing and constructing new parameterization schemes.

Significance Statement

Supersaturation is the fuel for the development of clouds in the atmosphere. In this paper, our goal is to better understand the supersaturation budget of clouds embedded in a turbulent environment by analyzing the basic equations of cloud microphysics. It is found that the turbulent characteristics of an air parcel substantially affect the cloud’s supersaturation budget and hence its life cycle. This is also shown in the context of mixed-phase clouds where, depending on the turbulent regime, different liquid-to-ice ratios are found. Consequently, the theoretical approach of this paper is crucial to develop tools to parameterize small-scale atmospheric features, like clouds, into global circulation models to improve climate projections for the future.

Open access
Chia Rui Ong
,
Makoto Koike
,
Tempei Hashino
, and
Hiroaki Miura

Abstract

In simulations of Arctic mixed-phase clouds, cloud persistence and the liquid water path (LWP) are sensitive to ice particle number concentrations. Here, we explore sensitivities of cloud microphysical properties to the dominant ice particle shape (dendrites, plates, columns, or spheres) using the SCALE-AMPS large-eddy simulation model. AMPS is a bin microphysics scheme that predicts particle shapes based on the inherent growth ratio (IGR) of spheroids, which determines vapor depositional growth rates along the a and c axes, and the rimed and aggregate mass fractions. We examine the impacts of various IGR values on simulations of clouds observed during the M-PACE and SHEBA experiments. Under M-PACE (SHEBA) conditions, LWP varies between 49 (1.1) and 230 (6.7) g m−2, and the ice water path (IWP) varies between 3 (0.03) and 40 (0.12) g m−2, depending on the ice shape. The lowest LWP and the highest IWP are obtained when columnar particles dominate because their low terminal velocities and large capacitance and collisional area result in large vapor deposition and riming rates, whereas the highest LWP and lowest IWP are obtained when spherical particles dominate because their vapor deposition and riming rates are low. Because ice particle shape significantly influences simulated Arctic mixed-phase clouds, reliable simulations require accurately estimated IGR values under various atmospheric conditions. Finally, comparisons between the simulation results and observations show that the size distribution larger than 2000 μm is better reproduced when the increase in rimed mass that causes ice particles to become spherical is suppressed.

Significance Statement

Atmospheric models have difficulties in reproducing Arctic mixed-phase clouds because of uncertainties in the parameterization of microphysical processes. This is the first study to use a large-eddy simulation model implemented with a habit-predicting bin microphysics scheme to demonstrate the important role of ice particle shape on the microphysical properties of both heavy-riming and no-riming mixed-phase clouds. We found the vapor deposition and riming rates to be greatly influenced by ice particle shape. By comparing the ice particle size distribution, mass–diameter relationship, and area ratio between simulation results and observations, we show that a hexagonal ice shape model and a riming model that simply converts ice crystals to graupel may not accurately reproduce actual heavy-riming clouds.

Open access
J. Federico Conte
,
Jorge L. Chau
,
Erdal Yiğit
,
José Suclupe
, and
Rodolfo Rodríguez

Abstract

One year of Spread spectrum Interferometric Multistatic meteor radar Observing Network (SIMONe) measurements are analyzed and compared for the first time between two low-latitude locations in Peru: Jicamarca (12°S, 77°W) and Piura (5°S, 80°W). Investigation of the mean horizontal winds and tides reveals that mesosphere and lower thermosphere (MLT) planetary-scale dynamics are similar between these two locations, although differences can be seen in some tidal components, e.g., the diurnal tide. On the other hand, 28-day median values of the momentum fluxes obtained with 4-h, 4-km time–altitude bins indicate that the mesoscale dynamics differ significantly between Jicamarca and Piura, places separated by approximately 850 km. From the middle of July until October 2021, a strong acceleration of the background zonal wind by westward-propagating gravity waves (GWs) is observed above ∼90 km at both locations, although with larger amplitudes over Jicamarca. From the middle of January until April 2022, a second strong acceleration of the background zonal wind, again by westward-propagating GWs, is observed, but this time with larger amplitudes over Piura. The latter is further supported by the dominance of negative vertical gradients of the zonal momentum flux above 89 km of altitude. Thus, these results observationally confirm the previous studies based on general circulation model simulations indicating that the directions of the zonal GW drag and the zonal background wind coincide in the low-latitude MLT. The weak correlations between the horizontal wind gradients over Jicamarca and Piura reinforce the fact that the mesoscale dynamics are different at these two locations.

Open access
Emily de Jong
,
Eliot Quon
, and
Shashank Yellapantula

Abstract

Low-level jets (LLJs), in which the wind speed attains a local maximum at low altitudes, have been found to occur in the U.S. mid-Atlantic offshore, a region of active wind energy deployment as of 2023. In contrast to widely studied regions such as the U.S. southern Great Plains and the California coastline, the mechanisms that underlie LLJs in the U.S. mid-Atlantic are poorly understood. This work analyzes floating lidar data from buoys deployed in the New York Bight to understand the characteristics and causes of coastal LLJs in the region. Application of the Hilbert–Huang transform, a frequency analysis technique, to LLJ case studies reveals that mid-Atlantic jets frequently occur during times of adjustment in synoptic-scale motions, such as large-scale temperature and pressure gradients or frontal passages, and that they do not coincide with motions at the native inertial oscillation frequency. Subsequent analysis with theoretical models of inertial oscillation and thermal winds further reveals that these jets can form in the stationary geostrophic wind profile from horizontal temperature gradients alone—in contrast to canonical LLJs, which arise from low-level inertial motions. Here, inertial oscillation can further modulate the intensity and altitude of the wind speed maximum. Statistical evidence indicates that these oscillations arise from stable stratification and the associated frictional decoupling due to warmer air flowing over a cold sea surface during the springtime land–sea breeze. These results improve our conceptual understanding of mid-Atlantic jets and may be used to better predict low-level wind speed maxima.

Significance Statement

The purpose of this work is to identify and characterize the atmospheric mechanisms that result in an occasional low-level maximum in the wind speed off the U.S. mid-Atlantic coastline. Our findings show that these low-level jets form due to horizontal temperature gradients arising from fronts and synoptic systems, as well as from the land–sea breeze that forces warmer air over the cold ocean surface. This work aids predictability of such jets, improves our understanding of this coastal environment, and has implications for future deployment of offshore wind energy in this region.

Open access