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Large‐scale weather forecasting and climate models are beginning to reach horizontal resolutions of kilometers, at which common assumptions made in existing parameterization schemes of subgrid‐scale turbulence and convection—such as that they adjust instantaneously to changes in resolved‐scale dynamics—cease to be justifiable. Additionally, the common practice of representing boundary‐layer turbulence, shallow convection, and deep convection by discontinuously different parameterizations schemes, each with its own set of parameters, has contributed to the proliferation of adjustable parameters in large‐scale models. Here we lay the theoretical foundations for an extended eddy‐diffusivity mass‐flux (EDMF) scheme that has explicit time‐dependence and memory of subgrid‐scale variables and is designed to represent all subgrid‐scale turbulence and convection, from boundary layer dynamics to deep convection, in a unified manner. Coherent up and downdrafts in the scheme are represented as prognostic plumes that interact with their environment and potentially with each other through entrainment and detrainment. The more isotropic turbulence in their environment is represented through diffusive fluxes, with diffusivities obtained from a turbulence kinetic energy budget that consistently partitions turbulence kinetic energy between plumes and environment. The cross‐sectional area of up and downdrafts satisfies a prognostic continuity equation, which allows the plumes to cover variable and arbitrarily large fractions of a large‐scale grid box and to have life cycles governed by their own internal dynamics. Relatively simple preliminary proposals for closure parameters are presented and are shown to lead to a successful simulation of shallow convection, including a time‐dependent life cycle. Key Points An extended eddy‐diffusivity mass‐flux (EDMF) scheme is presented that is prognostic and has variable plume area fractions The new EDMF scheme consistently partitions flow variables (including turbulence kinetic energy) between plumes and the environment In first tests, it successfully reproduces the average condition and transient life cycles of shallow convection

The planetary boundary layer (PBL) height (PBLH) is a key physical parameter of the PBL affected by numerous physical processes within the boundary layer. Specifically, the PBLH over land exhibits large spatial and temporal variation across different geographical regions. In this study, the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) radio occultation (RO) profiles and high-resolution radiosonde profiles from 2007 to 2013 were analyzed to estimate the diurnal cycle of the PBLH over the Southern Great Plains (SGP) in the United States. Large variations in PBLH derived from radiosonde temperature, moisture, and refractivity are observed on seasonal scales. COSMIC RO is capable of observing diurnal and seasonal variations in the terrestrial PBLH over the SGP region. Annual mean diurnal amplitude of approximately 250 m in the terrestrial PBLH was observed, with maxima occurring at around 1500 local solar time (LST) in both the collocated radiosondes and COSMIC RO profiles. Seasonal changes in the PBLH diurnal cycles ranging from approximately 100 to 400 m were also observed. Such PBL diurnal and seasonal changes can be further incorporated into PBL parameterizations to help improve weather and climate model prediction.

Deserts play an important role in the climate system, which is closely associated with the emission and transport of dust aerosols. Based on the intensive observation experiment in the Taklimakan Desert, the potential physical processes between the deep convective boundary layer (CBL) and dust emission are revealed in this study. Deep CBL enables the formation of clouds in the late afternoon, leading to significant cooling of surface. Large‐scale buoyant coherent structures thereby transform into the mechanical coherent structures confined near the surface. The responses promote the earlier occurrence of low‐level jet (LLJ) than in cloudless conditions, which allows the downward transport of LLJ momentum and substantially increases surface wind. Therefore, dust emission is initiated by strong wind at dusk and lasts for several hours. The results are useful to predict dust emissions and improve our understanding of distinctive boundary‐layer processes in desert regions. Plain Language Summary Desert is a key component of regional/global climate system, which is closely associated with the emission and transport of dust aerosols. A better understanding of dust emission mechanisms and their interaction with atmospheric physical processes is of great significance for improving numerical weather and climate models. This study investigates possible physical mechanisms of the dust emission related to deep atmosphere boundary layer, based on the field experiment in the Taklimakan Desert. It is found that the formation of late‐afternoon clouds and the occurrence of wind maxima at 400–600 m are crucial during the processes. Initially, the formation of clouds is enabled by deep atmosphere boundary layer that developed in the late afternoon. After cloud formation, surface becomes cooling, and then the upper part of the boundary layer is gradually released from the surface frictional restraint, which promotes the development of wind maxima at 400–600 m. As the momentum of the wind maxima is transported downwards, surface wind substantially increases, which systematically blows dust particles up. Consequently, dust emission happens at dusk in desert regions. Key Points Deep convective boundary layer enables the lifting condensation of moisture and the formation of boundary‐layer clouds in desert regions The emergence of late‐afternoon clouds strengthens the surface cooling and thus advances the development of low‐level jet Downward momentum transfer from low‐level jet to near‐surface wind is crucial to initiate dust emission at dusk

On 8 April 2024, a rare total solar eclipse (TSE) passed over western New York State (NYS), the first since 1925 and the last one until 2079. The NYS Mesonet (NYSM) consisting of 126 weather stations with 55 on the totality path provides unprecedented surface, profile, and flux data and camera images during the TSE. Here we use NYSM observations to characterize the TSE's impacts at the surface, in the planetary boundary layer (PBL), and on surface fluxes and CO2 concentrations. The TSE‐induced peak surface cooling occurs 17 min after the totality and is 2.8°C on average with a maximum of 6.8°C. It results in night‐like surface inversion, calm winds, and reduced vertical motion and mixing, leading to the shallowing of the PBL and its moistening. Surface sensible, latent and ground heat fluxes all decrease whereas near‐surface CO2 concentration rises as photosynthesis slows down. Plain Language Summary On 8 April 2024, a rare total solar eclipse (TSE) passed over western New York State (NYS), the first one since 1925 and the last one until 2079. The entire NYS witnessed at least 88% obscuration at the peak of the eclipse. It provides an excellent opportunity to study the impacts of the TSE. The NYS Mesonet (NYSM), an advanced statewide weather network, has 55 stations on the totality path and provides unprecedented measurements of surface meteorological variables, atmospheric vertical profiles, the heat exchange between the atmosphere and the surface and carbon dioxide (CO2) concentration. It enables one to study the TSE in greater details on a regional scale for the first time. This study found that the moon shadow cools the surface by as much as 6.8°C and creates a surface inversion layer. The cooling calms down winds and vertical mixing, leading to less escape of the water vapor and moistening of the air. It also reduces the heat exchange between the surface and the air. Without sunlight, the photosynthesis shuts down, causing a robust rise in near‐surface CO2 concentration. One‐minute camera images provide a fantastic view of the darkening of the sky during the TSE. Key Points The New York State Mesonet provided unprecedented surface, profile, flux and image data during the 8 April 2024 total solar eclipse across New York State The eclipse resulted in significant cooling and moistening near the surface and in the boundary layer, leading to a surface inversion layer It also weakened surface winds, turbulent mixing, heat fluxes, but caused a robust rise in near‐surface CO2 concentrations

Cold pools formed by precipitating convective clouds are an important source of mesoscale temperature variability. However, their sub‐mesoscale (100 m–10 km) structure has not been quantified, impeding validation of numerical models and understanding of their atmospheric and societal impacts. We assess temperature variability in observed and simulated cold pools using variograms calculated from dense network observations collected during a field experiment and in high‐resolution case‐study and idealized simulations. The temperature variance in cold pools is enhanced for spatial scales between ∼5 and 15 km compared to pre‐cold pool conditions, but the magnitude varies strongly with cold pool evolution and environment. Simulations capture the overall cold pool variogram shape well but underestimate the magnitude of the variability, irrespective of model resolution. Temperature variograms outside of cold pool periods are represented by the range of simulations evaluated here, suggesting that models misrepresent cold pool formation and/or dissipation processes. Plain Language Summary Cold pools are cool gusty winds beneath thunderstorms that are formed by cooling from rainfall. They have many important impacts in the atmosphere and on society but are difficult to properly simulate in numerical weather models. The variability in cold pool temperature is an understudied feature of cold pools but which is important to represent in numerical models. In this study, we examine cold pool temperature variability from a dense network of surface weather station observations collected during a field campaign, and we compare those observations to numerical simulations of cold pools in a range of environments. We find that cold pools enhance temperature variability for distances greater than ∼5 km but suppress variability on smaller distances, and that the magnitude of cold pool temperature variability is strongly dependent on the environment and cold pool lifetime. We also show that numerical models, even at very high resolutions, are not able to properly simulate the magnitude of cold pool temperature variability. We highlight areas for improvement in numerical models that may help to improve simulations of cold pool variability, including land‐atmosphere interactions, turbulence, and conversion processes between water vapor and condensed water in storms. Key Points Cold pool impacts on sub‐mesoscale temperature variability are quantified using variograms derived from observations and simulations Cold pools enhance temperature variability on scales between 5 and 15 km, but the magnitude varies strongly with lifetime and environment High‐resolution case‐study and idealized simulations underestimate the magnitude of cold pool variability, irrespective of resolution

Stratocumulus clouds are the most common type of boundary layer cloud; their radiative effects strongly modulate climate. Large eddy simulations (LES) of stratocumulus clouds often struggle to maintain fidelity to observations because of the sharp gradients occurring at the entrainment interfacial layer at the cloud top. The challenge posed to LES by stratocumulus clouds is evident in the wide range of solutions found in the LES intercomparison based on the DYCOMS‐II field campaign, where simulated liquid water paths for identical initial and boundary conditions varied by a factor of nearly 12. Here we revisit the DYCOMS‐II RF01 case and show that the wide range of previous LES results can be realized in a single LES code by varying only the numerical treatment of the equations of motion and the nature of subgrid‐scale (SGS) closures. The simulations that maintain the greatest fidelity to DYCOMS‐II observations are identified. The results show that using weighted essentially non‐oscillatory (WENO) numerics for all resolved advective terms and no explicit SGS closure consistently produces the highest‐fidelity simulations. This suggests that the numerical dissipation inherent in WENO schemes functions as a high‐quality, implicit SGS closure for this stratocumulus case. Conversely, using oscillatory centered difference numerical schemes for momentum advection, WENO numerics for scalars, and explicitly modeled SGS fluxes consistently produces the lowest‐fidelity simulations. We attribute this to the production of anomalously large SGS fluxes near the cloud tops through the interaction of numerical error in the momentum field with the scalar SGS model. Key Points Fidelity of LES simulations of stratocumulus clouds depends on advection schemes and SGS closures WENO schemes without explicit SGS closures simulate stratocumulus well A simple model shows how advection schemes and SGS closures interact and affect cloud simulations

In this work the very severe cyclonic storm Thane which formed over the Bay of Bengal during 25–31 December 2011 and struck the East coast of India was simulated using the Weather Research and Forecasting (WRF)-Advanced Research WRF (WRF-ARW) mesoscale model. Normally, very severe cyclones rarely form in this late season. The moisture transport, intensity, track and structure of the cyclone is analyzed through vertically integrated moisture flux convergence and planetary boundary layer physics of the Yonsei University (YSU), Mellor–Yamada–Janjic (MYJ) and Asymmetrical Convective Model version 2 (ACM2) schemes. Cyclonic circulation and moisture convergence are seen 6 days ahead of the development of the cyclone and strengthened by the transport of moisture advected from the South China Sea. From the three planetary boundary layer (PBL) schemes, the YSU scheme gives better results both qualitatively and quantitatively for the moisture flux convergence. The MYJ scheme produced the least errors for cyclone intensity from genesis to the landfall stage, while the ACM2 scheme gave better results after landfall. The track of the cyclone with the YSU scheme produced the least errors throughout the life cycle which gives the least landfall error. The structure of the cyclone in terms of tangential winds, the spatial distribution of cloud bands, vertical cross section of temperature anomaly, relative humidity and vertical winds was well simulated by the ACM2 scheme.

Global reanalyzes like ERA5 accurately capture atmospheric processes at spatial scales of O(10)$\\mathcal{O}(10)$  km or larger. By downscaling ERA5 with large‐eddy simulation (LES), LES can provide details about processes at spatio‐temporal scales down to meters and seconds. Here, we present an open‐source Python package named the “Large‐eddy simulation and Single‐column model—Large‐Scale Dynamics,” or (LS)2D in short, designed to simplify the downscaling of ERA5 with doubly‐periodic LES. A validation with observations, for several sensitivity experiments consisting of month‐long LESs over Cabauw (the Netherlands), demonstrates both its usefulness and limitations. The day‐to‐day variability in the weather is well captured by (LS)2D and LES, but the setup under‐performs in conditions with broken or near overcast clouds. As a novel application of this modeling system, we used (LS)2D to study surface solar irradiance variability, as this quantity directly links land‐surface processes, turbulent transport, and clouds, to radiation. At a horizontal resolution of 25 m, the setup reproduces satisfactorily the solar irradiance variability down to a timescale of seconds. This demonstrates that the coupled LES‐ERA5 setup is a useful tool that can provide details on the physics of turbulence and clouds, but can only improve on its host reanalysis when applied to meteorological suitable conditions. Plain Language Summary Modern global weather models are accurate in predicting atmospheric processes at scales of around 10 km or larger, but are less good at predicting smaller scale processes, like for example, the interaction between solar radiation, individual clouds, and the resulting clouds shadows that are cast onto the land surface. High spatio‐temporal resolution research models are able to capture these smaller scale processes, but require a coupling to a weather model to account for the day‐to‐day variability in our weather. In this paper, we present a framework to couple large to small scale models, and demonstrate both the benefits and challenges of using this coupled model setup. The coupled setup excels in capturing the aforementioned high frequency interactions between small clouds and surface solar radiation. However, the chaotic nature of broken to overcast clouds is proven difficult to represent. The coupled model setup is published as open‐source code, and is therefore freely available to the research community. Key Points We developed an open‐source Python package named (LS)2D, designed to downscale the ERA5 reanalysis with turbulence and cloud‐resolving large‐eddy simulation (LESs) One month long experiments with (LS)2D and MicroHH over the Netherlands demonstrate both the skill and limitations of the coupled setup Capturing high‐frequency interactions between clouds and surface solar irradiance requires high resolution (O$\\mathcal{O}$ (10) m) LES

We present nonrotating simulations with the Goddard Earth Observing System (GEOS) atmospheric general circulation model (AGCM) in a square limited area domain over uniform sea surface temperature. As in previous studies, convection spontaneously aggregates into humid clusters, driven by a combination of radiative and moisture‐convective feedbacks. The aggregation is qualitatively independent of resolution, with horizontal grid spacing from 3 to 110 km, with both explicit and parameterized deep convection. A budget for the spatial variance of column moist static energy suggests that longwave radiative and surface flux feedbacks help establish aggregation, while the shortwave feedback contributes to its maintenance. Mechanism‐denial experiments confirm that aggregation does not occur without interactive longwave radiation. Ice cloud radiative effects help support the humid convecting regions but are not essential for aggregation, while liquid clouds have a negligible effect. Removing the dependence of parameterized convection on tropospheric humidity reduces the intensity of aggregation but does not prevent the formation of dry regions. In domain sizes less than (5,000 km)2, the aggregation forms a single cluster, while larger domains develop multiple clusters. Larger domains initialized with a single large cluster are unable to maintain them, suggesting an upper size limit. Surface wind speed increases with domain size, implying that maintenance of the boundary layer winds may limit cluster size. As cluster size increases, large boundary layer temperature anomalies develop to maintain the surface pressure gradient, leading to an increase in the depth of parameterized convective heating and an increase in gross moist stability. Key Points The sensitivity of parameterized convection to midtropospheric humidity enhances aggregation Humid clusters have a maximum scale of 3–4,000 km, limited by the boundary layer momentum balance Larger clusters have warmer humid‐region boundary layers and deeper convective heating

The diurnal cycle of environmental conditions for shallow and deep convection regimes within the Indian monsoon environment is investigated using comprehensive observations from the surface, boundary layer, and cloud layers. For shallow convection (SC) and deep convection (DC) in the afternoon hours, thermodynamics, moisture convergence, and several other environmental variables provide information on the factors that control the vertical extent of convection in both regimes. The SC regime is characterized by high sensible heat flux, leading to stronger boundary layer turbulence, a higher mixed layer, and increased dry air entrainment from the free troposphere. Evaluation of several pre-conditioning parameters with T-test statistics suggests that stronger mid-level meridional wind shear and lack of mid-level moistening are detrimental to the growth of clouds in the SC regime. Conversely, the DC regime is driven by low surface fluxes and low surface-level buoyancy, with higher boundary layer and mid-layer moisture and more mid-layer instability, supporting larger Convective Available Potential Energy (CAPE). Morning precursor conditions for the preference of SC versus DC regime in the afternoon reveal that total column water vapor, relative humidity and CAPE are significantly higher on DC days. Large-scale moisture transport in the early morning within and above the boundary layer, driven by stronger westerly winds, is a key factor for the development of DC later in the day. This investigation enhances our understanding of boundary layer controls on shallow and deep convection within the Indian Monsoon environment.