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At least 199 records · Page 11

A Novel Method for Diagnosing Land–Atmosphere Coupling Sensitivity in a Single-Column Model

The response of boundary layer properties and cloudiness to changes in surface evaporative fraction (EF) is investigated in a single-column model to quantify the locally coupled impact of subgrid surface variations on the atmosphere during summer. Sensitive coupling days are defined when the model atmosphere exhibits large variations across a range of EFs centered on the analyzed value. Coupling sensitivity exists as both positive feedback (cloudiness increases with EF) and negative feedback (clouds increase with decreasing EF) regimes. The positive regime manifests in shallow convection situations, which are capped by a strengthened inversion and subsidence, restricting the vertical extent of convection to just above the boundary layer. Surfaces with larger EF (greater surface latent heat flux) can inject more moisture into the vertically confined system, lowering the cloud base and an increasing cloud liquid water path (LWP). Negative feedback regimes tend to manifest when large-scale deep convection, such as from mesoscale convective systems and fronts, is advected through the domain, where convection strengthens over surfaces with a lower EF (greater surface sensible heat flux). The invigoration of these systems by the land surface leads to an increase in LWP through strengthened updrafts and stronger coupling between the boundary layer and the free atmosphere. These results apply in the absence of heterogeneity-induced mesoscale circulations, providing a one-dimensional dynamical perspective on the effect of surface heterogeneity. Finally, this study provides a framework of intermediate complexity, lying between parcel theory and high-resolution coupled land–atmosphere modeling, and therefore isolates the relevant first-order processes in land–atmosphere interactions.

54 ENVIRONMENTAL SCIENCES↗

Air pollutant transport in a coastal environment. Part 1: Two-dimensional simulations of sea-breeze and mountain effects

Over the southern California coastal region, observations of the vertical distributions of pollutants show that maximum concentrations can occur within temperature inversion layers well above the surface. A mesoscale model is used to study the dynamical phenomena that cause such layers, including sea breezes and mountain flows, and to study the characteristics of air pollutant transport in a coastal environment capped by a temperature inversion. The mathematical and physical structure of the model is described. Two-dimensional simulations corresponding to four configurations of coastal plains and mountains are discussed. The simulations reveal that pollutant transport over a coastal plain is strongly influenced by the topographic configuration, including the height of coastal mountains and their distance from the coastline. Sea breezes induced by land-sea thermal contrasts, as well as upslope winds induced along mountain flanks, both create vertical transport that can lead to the formation of elevated pollution layers. The sea-breeze circulation generates pollution layers by undercutting the mixed layer and lofting pollutants into the stable layer. Heating of mountain slopes acts to vent pollutants above the mountain ridge during the day; during the evening, pollutants can be injected directly into the inversion layer from the decaying upslope flows. In a land-sea configuration with mountains close to the coastline, the sea breeze and heated-mountain flow are strongly coupled. In the afternoon, this interaction can produce upslope flow from which polluted air is detrained into the inversion layer as a return circulation. When the mountains lie farther inland, however, pollutants may be trapped aloft when the mixed layer stabilizes in the late afternoon. As the nocturnal boundary layer forms over the coast in the evening, polluted mixed-layer air is effectively left behind in the inversion layer. In the Los Angeles Basin, the formation mechanism for elevated polluted layers is most similar to our cases with inland mountains.

Lu, Rong↗

Perpendicular crossing chains enable high mobility in a noncrystalline conjugated polymer

The nature of interchain π-system contacts, and their relationship to hole transport, are elucidated for the high-mobility, noncrystalline conjugated polymer C16-IDTBT by the application of scanning tunneling microscopy, molecular dynamics, and quantum chemical calculations. The microstructure is shown to favor an unusual packing motif in which paired chains cross-over one another at near-perpendicular angles. By linking to mesoscale microstructural features, revealed by coarse-grained molecular dynamics and previous studies, and performing simulations of charge transport, it is demonstrated that the high mobility of C16-IDTBT can be explained by the promotion of a highly interconnected transport network, stemming from the adoption of perpendicular contacts at the nanoscale, in combination with fast intrachain transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Satellite Altimeter Observations of Black Sea Level Variations

Satellite altimeter data from TOPEX/POSEIDON and ERS-1 are used to examine seasonal and mesoscale variability of the Black Sea level. Consistent processing procedures of the altimeter measurements make it possible to determine the dynamical Black Sea level with an rms accuracy about 3 cm. It is shown that the Black Sea circulation intensifies in the winter-spring seasons and attenuates in summer-autumn. The seasonal variability of sea level is accompanied by a radiation of Rossby waves from the eastern coast of the basin. Mesoscale oscillations of the dynamical sea level are found to vary spatially and temporarily. Usually, strong eddy intensity is associated with instabilities of the Rim Current. Away from this circulation feature, in the deep basin, mesoscale variability is much smaller. Mesoscale variability has a strong seasonal signal, which is out of phase with the strength of the Rim Current.

Korotaev, G. K.↗

Future possibilities in objective analysis and data assimilation for atmospheric dynamics

The role that dynamics plays in estimating the state of the atmosphere from incomplete and noisy data is reviewed. Objective analysis represents an attempt at relying mostly on the data and minimizing the role of dynamics in the estimation. Data assimilation tries to balance properly the roles of dynamical and observational information. Sequential estimation is presented as the proper framework for understanding this balance, and the Kalman filter as the ideal, optimal procedure for data assimilation. The optimal filter computes forecast error covariances of a given atmospheric model exactly, and hence data assimilation should be closely connected with predictability studies. This connection is described, and consequences drawn for currently active areas of the atmospheric and related sciences, namely, mesoscale meteorology, long range forecasting, and upper ocean dynamics. Possibilities offered by judicious data assimilation in understanding barotropic adjustment, a phenomenon that appears to play a crucial role in atmospheric behavior on the scale of weeks to months, and hence in long range forecasting are addressed.

Ghil, M.↗

Investigating shock-induced chemical reactions in Ni+Al multilayers: A continuum-based mesoscale approach with Arrhenius kinetics and artificial thermal conduction

A new continuum-based mesoscale modeling approach for shock-induced chemical reactions (SICRs) in Ni+Al multilayers is demonstrated in Sandia’s shock physics hydrocode, CTH. The approach utilizes Arrhenius-type kinetics and artificial thermal conduction. Our work builds upon previous efforts to parameterize equations of state for Ni x Al y [J. Appl. Phys. 137, 075102 (2025)], as well as simulations of inert shocks in realistic 2D microstructures [J. Appl. Phys. 137, 225301 (2025)]. To calibrate the reaction kinetics, pairs of the reaction coordinate, R′, vs time are extracted from the molecular dynamics (MD) literature. Here, the MD-informed kinetics are used to simulate the dynamic evolution of pressure and temperature in 2D mesoscale simulations. Overall, the MD-informed kinetics obtained for planar interfaces are too slow, as initial reaction is not observed on a nanosecond time scale. Even with quasi-periodic shock focusing leading to the formation of so-called “hot-spots,” the hot spots are unable to grow and coalesce using the fitted Arrhenius rate constants. However, by increasing the rate constants by two orders of magnitude, SICRs are observed at a shock pressure near 30 GPa, which is supported by experiments. Consequently, these mesoscale simulations suggest that unresolved shear-based mechanical mixing might possibly account for the discrepancies in kinetic rates, with shock-generated intense perturbations, interfacial vortical flows, and elevated temperatures serving as favorable reaction conditions. Future work will calibrate a shear-dependent reaction rate from the MD simulations with realistic interfaces that are wavy, diffuse, and disordered.

Kittell, David E. [Sandia National Laboratories (S↗

Regional aeolian dynamics and sand mixing in the Gran Desierto - Evidence from Landsat Thematic Mapper images

Mesoscale mapping of spatial variations in sand composition of the Gran Desierto (Sonora, Mexico) was carried out on multispectral Landsat TM images of this region, making it possible to examine the dynamic development of sand sheets and dunes. Compositions determined from remote imagery were found to agree well with samples from selected areas. The sand populations delineated were used to describe the sediment source areas, transport paths, and deposition sites. The image analysis revealed important compositional variations aver large areas that were not readily apparent in the field data.

Blount, Grady↗

Active-noise-induced dynamic clustering of passive colloidal particles

Active fluids generate spontaneous, often chaotic mesoscale flows. Harnessing these flows to drive soft materials embedded within an active fluid into structures with controlled length scales and lifetimes is a key challenge at the interface between the fields of active matter and nonequilibrium self-assembly. Here, we present a simple and efficient computational approach to model soft materials advected by active fluids, by simulating particles moving in a spatiotemporally correlated noise field. To illustrate our approach, we simulate the dynamical self-organization of repulsive colloids within such an active noise field. The colloids form structures whose sizes and dynamics can be tuned by the correlation time and length of the active fluid, and range from small rotating droplets to clusters with internal flows and system-spanning sizes that vastly exceed the active correlation length. Our results explain how the interplay between active fluid time and length scales and emergent driven assembly can be used to rationally design functional assemblies. More broadly, our approach can be used to efficiently simulate diverse active fluids and other systems with spatiotemporally correlated noise.

Brownian dynamics↗

The Surface Water and Ocean Topography Mission

The SWOT mission is a partnership between two communities, physical oceanography and hydrology, to share high vertical accuracy and high spatial resolution topography data produced by the science payload, whose principal instrument is a Ka-band radar Interferometer. The SWOT mission will provide large-scale data sets of ocean sea-surface height resolving scales of 15km (in wavelength) and larger, allowing the characterization of ocean mesoscale and submesoscale circulation. Present altimeter constellations can only resolve the ocean circulation at wavelengths larger than 200km. SWOT will address fundamental questions on the dynamics of ocean variability at wavelengths shorter than 200km, which encompasses mesoscale and submesoscale processes such as the formation, evolution, and dissipation of eddy variability (including narrow currents, fronts, and quasi-geostrophic turbulence) and their role in air-sea interaction.

Zohar, Guy↗

Development of a severe local storm prediction system: A 60-day test of a mesoscale primitive equation model

The progress and problems associated with the dynamical forecast system which was developed to predict severe storms are examined. The meteorological problem of severe convective storm forecasting is reviewed. The cascade hypothesis which forms the theoretical core of the nested grid dynamical numerical modelling system is described. The dynamical and numerical structure of the model used during the 1978 test period is presented and a preliminary description of a proposed multigrid system for future experiments and tests is provided. Six cases from the spring of 1978 are discussed to illustrate the model's performance and its problems. Potential solutions to the problems are examined.

Paine, D. A.↗

Mesoscale Convective Systems in DYAMOND Global Convection‐Permitting Simulations

Abstract This study examines the deep convection populations and mesoscale convective systems (MCSs) simulated in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non‐hydrostatic domains) winter project. A storm tracking algorithm is applied to six DYAMOND simulations and a global high‐resolution satellite cloud and precipitation data set for comparison. The simulated frequencies of tropical deep convection and organized convective systems vary widely among models and regions, although robust MCSs are generally underestimated. The diurnal cycles of MCS initiation and mature stages are well simulated, but the amplitudes are exaggerated over land. Most models capture the observed MCS lifetime, cloud shield area, rainfall volume and movement speed. However, cloud‐top height and convective rainfall intensity are consistently overestimated, and stratiform rainfall area and amount are consistently underestimated. Possible causes for the model differences compared to observations and implications for future model developments are discussed.

58 GEOSCIENCES↗

Improving High-Resolution Weather Forecasts using the Weather Research and Forecasting (WRF) Model with an Updated Kain-Fritsch Scheme

Efforts to improve the prediction accuracy of high resolution (1-10 km) surface precipitation distribution and variability are of vital importance to local aspects of air pollution, wet deposition, and regional climate. However, precipitation biases and errors can occur at these spatial scales due to uncertainties in initial meteorological conditions and/or grid-scale cloud microphysics schemes. In particular, it is still unclear to what extent a subgrid-scale convection scheme could be modified to bring in scale-awareness for improving high-resolution short-term precipitation forecasts in the WRF model. To address these issues, we introduced scale-aware parameterized cloud dynamics for high-resolution forecasts by making several changes to the Kain-Fritsch (KF) convective parameterization scheme in the WRF model. These changes include subgrid-scale cloud-radiation interactions, a dynamic adjustment timescale, impacts of cloud updraft mass fluxes on grid-scale vertical velocity, and lifting condensation level-based entrainment methodology that includes scale dependency. A series of 48-hour retrospective forecasts using a combination of three treatments of convection (KF, updated KF, and the use of no cumulus parameterization), two cloud microphysics schemes and two types of initial condition datasets were performed over the U.S. southern Great Plains on 9- and 3-km grid spacings during the summers of 2002 and 2010. Results indicate that (1) the source of initial conditions play a key role in high-resolution precipitation forecasting, and (2) our updated KF scheme greatly alleviates the excessive precipitation at 9-km grid spacing and improves results at 3-km grid spacing as well. Overall, we found that the updated KF scheme incorporated into a high-resolution model does provide better forecasts for precipitation location and intensity.

convective parameterization↗

Space Technology 5 Multipoint Observations of Temporal and Spatial Variability of Field-Aligned Currents

Space Technology 5 (ST5) is a constellation mission consisting of three microsatellites. It provides the first multipoint magnetic field measurements in low Earth orbit, which enables us to separate spatial and temporal variations. In this paper, we present a study of the temporal variability of field-aligned currents using the ST5 data. We examine the field-aligned current observations during and after a geomagnetic storm and compare the magnetic field profiles at the three spacecraft. The multipoint data demonstrate that mesoscale current structures, commonly embedded within large-scale current sheets, are very dynamic with highly variable current density and/or polarity in approx.10 min time scales. On the other hand, the data also show that the time scales for the currents to be relatively stable are approx.1 min for mesoscale currents and approx.10 min for large-scale currents. These temporal features are very likely associated with dynamic variations of their charge carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of mesoscale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Le, G.↗

TRMM Validation: Integration of TRMM Satellite and Ground-Validation Data to Determine Tropical Heating

Steiner and Houze showed from ground validation data that the Tropical Rain Measuring Mission (TRMM) satellite Precipitation Radar's (PR's) twice daily only sampling should lead to an uncertainty of approximately 20% in rain estimates. They further showed that the uncertainties are smallest at the 5-7.5 km level. Schumacher and Houze used Kwajalein ground validation data to show that the TRMM PR misses only 2.3% of the near surface rainfall but does not see 46% of the area where rain occurs, because of the 17 dBZ PR reflectivity threshold. Houze discusses how the TRMM data extend earlier tropical convective studies to global coverage of the vertical profile of latent heating via the TRMM PR''s ability to distinguish and globally map convective and stratiform precipitation. Process studies carried out under this TRMM grant Yuter and Houze and Yuter et al. studied ship-based radar observations in the tropical eastern Pacific ITCZ. The eastern Pacific precipitation process is different from the western Pacific (the COARE area); rain is heavier but the clouds are not as deep. These process differences may affect the ability to remotely sense precipitation accurately in the two regions. Satellite microwave data were able to detect the precipitation as long as the rain areas exceeded 10 km in dimension. However, the microwave algorithms had difficulty distinguishing light and heavy rain. Satellite IR algorithms only partially detected the rain because the tops of the smaller and more short-lived rain clouds were sometimes not cold enough for the IR algorithms to detect them. Houze et al. focused on the west Pacific precipitating mesoscale convective systems and showed how their precipitation and internal dynamics vary in relation to the slowly varying large-scale heating-driven circulation, which has a structure described by a combination of Kelvin and Rossby wave response to the near-equatorial convective heating constituted by the mesoscale convective systems. Ship and aircraft radar data were used in this study.

Houze, Robert A., Jr.↗

Ab initio generalized Langevin equation

We introduce a machine learning–based approach called ab initio generalized Langevin equation (AIGLE) to model the dynamics of slow collective variables (CVs) in materials and molecules. In this scheme, the parameters are learned from atomistic simulations based on ab initio quantum mechanical models. Force field, memory kernel, and noise generator are constructed in the context of the Mori–Zwanzig formalism, under the constraint of the fluctuation–dissipation theorem. Combined with deep potential molecular dynamics and electronic density functional theory, this approach opens the way to multiscale modeling in a variety of situations. Here, we demonstrate this capability with a study of two mesoscale processes in crystalline lead titanate, namely the field-driven dynamics of a planar ferroelectric domain wall, and the dynamics of an extensive lattice of coarse-grained electric dipoles. In the first case, AIGLE extends the reach of ab initio simulations to a regime of noise-driven motions not accessible to molecular dynamics. In the second case, AIGLE deals with an extensive set of CVs by adopting a local approximation for the memory kernel and retaining only short-range noise correlations. The scheme is computationally more efficient than molecular dynamics by several orders of magnitude and mimics the microscopic dynamics at low frequencies where it reproduces accurately the dominant far-infrared absorption frequency.

97 MATHEMATICS AND COMPUTING↗

Mesoscale Convective Systems Tracking Method Intercomparison (MCSMIP): Application to DYAMOND Global km‐Scale Simulations

Abstract Global kilometer‐scale models represent the future of Earth system modeling, enabling explicit simulation of organized convective storms and their associated extreme weather. Here, we comprehensively evaluate tropical mesoscale convective system (MCS) characteristics in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non‐hydrostatic domains) simulations for both summer and winter phases. Using 10 different feature trackers applied to simulations and satellite observations, we assess MCS frequency, precipitation, and other key characteristics. Substantial differences (a factor of 2–3) arise among trackers in observed MCS frequency and their precipitation contribution, but model‐observation differences in MCS statistics are more consistent across trackers. DYAMOND models are generally skillful in simulating tropical mean MCS frequency, with multi‐model mean biases ranging from −2%–8% over land and −8%–8% over ocean (summer vs. winter). However, most DYAMOND models underestimate MCS precipitation amount (23%) and their contribution to total precipitation (17%). Biases in precipitation contributions are generally smaller over land (13%) than over ocean (21%), with moderate inter‐model variability. While models better simulate MCS diurnal cycles and cloud shield characteristics, they overestimate MCS precipitation intensity and underestimate stratiform rain contributions (up to a factor of 2), particularly over land, albeit observational uncertainties exist. Additionally, models exhibit a wide range of precipitable water in the tropics compared to reanalysis and satellite observations, with many models showing exaggerated sensitivity of MCS precipitation intensity to precipitable water. The MCS metrics developed here provide process‐oriented diagnostics to guide future model development.

54 ENVIRONMENTAL SCIENCES↗

Analysis and modeling of summertime convective cloud and precipitation structure over the Southeastern United States

A summary of an investigation of deep convective cloud systems that typify the summertime subtropical environment of northern Alabama is presented. The major portion of the research effort included analysis of data acquired during the 1986 Cooperative Huntsville Meteorological Experiment (COHMEX), which consisted of the joint programs Satellite Precipitation and Cloud Experiment (SPACE) under NASA direction, the Microburst and Service Thunderstorm (MIST) Program under NSF sponsorship, and the FAA-Lincoln Laboratory Weather Study (FLOWS). This work relates closely to the SPACE component of COHMEX, one of the general goals of which was to further the understanding of kinematic and precipitation structure of convective cloud systems. The special observational plateforms that were available under the SPACE/COHMEX Program are shown. The original objectives included studies of both isolated deep convection and of (small) mesoscale convection systems that are observed in the Southeast environment. In addition, it was proposed to include both observational and comparative numerical modeling studies of these characteristic cloud systems. Changes in scope were made during the course of this investigation to better accommodate both the manpower available and the data that was acquired. A greater emphasis was placed on determination of the internal structure of small mesoscale convective systems, and the relationship of internal dynamical and microphysical processes to the observed cloud top behavior as inferred from GOES IR (30 min) data. The major accomplishments of this investigation are presented.

Knupp, Kevin R.↗

Breaking Wave Field Statistics With A Multi-Layer Model

The statistics of breaking wave fields are characterised within a novel multi-layer framework, which generalises the single-layer Saint-Venant system into a multi-layer and non-hydrostatic formulation of the Navier–Stokes equations. We simulate an ensemble of phase-resolved surface wave fields in physical space, where strong nonlinearities, including directional wave breaking and the subsequent highly rotational flow motion, are modelled, without surface overturning. We extract the kinematics of wave breaking by identifying breaking fronts and their speed, for freely evolving wave fields initialised with typical wind wave spectra. The Λ(c) distribution, defined as the length of breaking fronts (per unit area) moving with speed c to c + dc following Phillips (J. Fluid Mech., vol. 156, 1985, pp. 505–531), is reported for a broad range of conditions. We recover the Λ(c) ∝ c−6 scaling without wind forcing for sufficiently steep wave fields. A scaling of Λ(c) based solely on the root-mean-square slope and peak wave phase speed is shown to describe the modelled breaking distributions well. The modelled breaking distributions are in good agreement with field measurements and the proposed scaling can be applied successfully to the observational data sets. The present work paves the way for simulations of the turbulent upper ocean directly coupled to a realistic breaking wave dynamics, including Langmuir turbulence, and other sub-mesoscale processes.

Jiarong Wu↗