Empirical relationship between entrainment rate and microphysics in cumulus clouds
N/A
54 ENVIRONMENTAL SCIENCES↗
SEARCH · Engineering Papers
Results for “cloud microphysics”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Maritime Cloud and Drizzle Microphysical Properties Retrieved From Ship-Based Observations During MAGIC
Explore the source record for details and available documents.
54 ENVIRONMENTAL SCIENCES↗
Sensitivity of Arctic Clouds to Ice Microphysical Processes in the NorESM2 Climate Model
Explore the source record for details and available documents.
54 ENVIRONMENTAL SCIENCES↗
Training the Next Generation of Researchers in Exploring Cloud Dynamics and Microphysics Using Millimeter-Wavelength Radars
Explore the source record for details and available documents.
54 ENVIRONMENTAL SCIENCES↗
Observed and Simulated Variability of Droplet Spectral Dispersion in Convective Clouds Over the Amazon
Abstract In this study, the variability of the spectral dispersion of droplet size distributions (DSDs) in convective clouds is investigated. Analyses are based on aircraft measurements of growing cumuli near the Amazon basin, and on numerical simulations of an idealized ice‐free cumulus. In cleaner clouds, the relative dispersion , defined as the ratio of the standard deviation to the mean value of the droplet diameter, is negatively correlated with the ratio of the cloud water content ( ) to the adiabatic liquid water content ( ), while no strong correlation between and is seen in polluted clouds. Bin microphysics numerical simulations suggest that these contrasting behaviors are associated with the effect of collision‐coalescence in cleaner clouds, and secondary droplet activation in polluted clouds, in addition to the turbulent mixing of parcels that experienced different paths within the cloud. Collision‐coalescence simultaneously broadens the DSDs and decreases , explaining the inverse relationship between and in cleaner clouds. Secondary droplet activation broadens the DSDs but has little direct impact on . The combination of a rather modest DSD broadening due to weak collision‐coalescence with enhanced droplet activation in both diluted and highly undiluted cloud regions may contribute to maintain a relatively uniform within polluted clouds. These findings can be useful for parameterizing the shape parameter ( ) of gamma DSDs in bulk microphysics cloud‐resolving models. It is shown that emulating the observed relationship improves the estimation of the collision‐coalescence rate in bulk microphysics simulations compared to the bin simulations.
54 ENVIRONMENTAL SCIENCES↗
A Machine Learning Framework for Predicting Microphysical Properties of Ice Crystals From Cloud Particle Imagery
The microphysical properties of ice crystals are important because they significantly alter the radiative properties and spatiotemporal distributions of clouds, which in turn strongly affect Earth's climate. However, it is challenging to measure key properties of ice crystals, such as mass or morphological features. Here, we present a proof-of-concept framework for predicting three-dimensional (3D) microphysical properties of ice crystals from in situ two-dimensional (2D) imagery. First, we computationally generated synthetic ice crystals using 3D modeling software along with geometric parameters estimated from the 2021 Ice Cryo-Encapsulation Balloon (ICEBall) field campaign. Then, we used synthetic crystals to train machine learning (ML) models to predict effective density ($ρ_e$), effective surface area ($A_e$), and number of bullets ($N_b$) from synthetic rosette imagery. On unseen synthetic images, our ML models accurately predicted ice crystal properties. ResNet-18 performed best, achieving $R^2$ values of 0.99 and 0.98 for $ρ_e$ and $A_e$, respectively, and MAE of 0.10 for mathematical equation in single view tasks. Stereo view ResNet-18 further reduced RMSE by 40% for $ρ_e$ and $A_e$ and reduced MAE by 0.08 for $N_b$. This work provides a novel ML-driven framework for estimating ice microphysical properties from in situ imagery, which will allow for downstream constraints on microphysical parameterizations, such as the mass-size relationship.
Ko, J. [Columbia Univ., New York, NY (United State↗
Retrieval of Boundary Layer 3D Cloud Properties Using Scanning Cloud Radar and 3D Radiative Transfer
Retrievals of cloud optical and microphysical properties for boundary layer clouds, including those widely used by ASR investigators, frequently assume that clouds are sufficiently horizontally homogeneous that scattering and absorption (at all wavelengths) can be treated using one dimensional (1D) radiative transfer, and that differences in the field-of-view of different sensors are unimportant. Unfortunately, most boundary layer clouds are far from horizontally homogeneous, and numerous theoretical and observational studies show that the assumption of horizontal homogeneity leads to significant errors. The introduction of scanning cloud and precipitation radars at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program sites presents opportunities to move beyond the horizontally homogeneous assumption. The primary objective of this project was to develop a 3D retrieval for warm-phase (liquid only) boundary layer cloud microphysical properties, and to assess errors in current 1D (non-scanning) approaches. Specific research activities also involved examination of the diurnal cycle of hydrometeors as viewed by ARM cloud radar, and continued assessment of precipitation impacts on retrievals of cloud liquid water path using passive microwaves.
54 ENVIRONMENTAL SCIENCES↗
Improving parameterization of ice microphysical processes in Arctic clouds using a synergistic modeling and observational approach (Final Report)
The primary goals of the project were to: 1) Improve the fundamental quantitative models of ice growth processes using ARM radar observations. 2) Better understand the growth of ice particle populations through vapor deposition, riming, and aggregation in Arctic clouds using a new particle-property microphysical model. 3) Robustly estimate and constrain key unknown model parameters using ARM radar observations combined with the particle-property model to develop an improved parameterization of ice growth processes for traditional bulk parameterizations used in cloud and climate models.
58 GEOSCIENCES↗
A Computationally Efficient Linear Semi-Lagrangian Scheme for the Advection of Microphysical Variables in Cloud-Resolving Models
An efficient semi-Lagrangian (SL) numerical scheme for the advection of positive-definite microphysical variables in cloud-resolving models is proposed. The scheme is a linear combination of SL schemes of the first and second order. The proposed scheme is compared with two high-order, monotonic, nonlinear Eulerian schemes, in two 2D tests. In the first test, advection of a positive scalar field with large gradients is performed within complicated idealized steering flows. In the second test, a hail storm is simulated using the 2D Hebrew University Cloud Model, describing the interactions between 15 size distributions of different microphysical quantities (each distribution is described by 43 mass bins). The proposed scheme is computationally efficient, has a low numerical diffusion and a high level of mass conservation accuracy, and preserves the sum of multiple advected variables as well as the linear relationships between the advected scalar variables. Although the proposed SL scheme is not exactly positive definite, the negative values and their number, which may appear only in the case of very strong gradients, are negligible. The scheme produces results similar to those of nonlinear Eulerian advection schemes while reducing computation time by approximately a factor of 10.
54 ENVIRONMENTAL SCIENCES↗
Parameterizations of Depositional Growth of Cloud Ice in a Bulk Microphysical Scheme
The conversion of cloud ice to snow by depositional growth, designated P(sub SFI), in the Goddard Cumulus Ensemble Model cloud physics parameterization is examined. The original formulation of P(sub SFI) is shown to produce excessive conversion of cloud ice to snow because of an implicit assumption that the relative humidity is 100% with respect to water even though the air may actually be quite less humid. Two possible corrections to this problem are proposed, the first involving application of a relative humidity dependent correction factor to the original formulation of P(sub SFI), and the second involving a new formulation of P(sub SFI) based on the equation for depositional growth of cloud ice.
Braun, Scott A.↗
First EarthCARE CPR Observations of Dynamics–Microphysics Coupling in Marine Cold‐Air Outbreak Clouds
Marine cold-air outbreak (MCAO) clouds begin as shallow cloud streets near the ice edge and evolve into broken open-cell convection downstream. Their rapid transitions in cloud structure and microphysics are closely linked to vertical motions, but this interplay has not previously been observed from space. The EarthCARE satellite, carrying the first spaceborne Doppler radar (Cloud Profiling Radar, CPR), now measures hydrometeor sedimentation velocity and vertical air motion. Using CPR observations over the Norwegian and Barents Seas (December 2024–May 2025), we analyze MCAO and non-MCAO clouds. We find that strong updrafts in MCAO clouds coincide with larger supercooled liquid water (SLW) path (LWP). These conditions are accompanied by increases in sedimentation velocity and its vertical gradient, reflecting rapid riming-driven ice growth. In contrast, non-MCAO clouds show lower riming efficiency at similar LWP due to relatively weaker dynamical support. This emphasizes the importance of dynamics in shaping polar cloud structure and microphysics.
Kim, Jiseob [McGill Univ., Montreal, QC (Canada)] ↗
Effects of Sea Spray on Microphysics and Intensity of Deep Convective Clouds Under Strong Winds
Deep convective clouds similar to those arising in the tropical cyclone eyewall are simulated using a parcel model and 2–D slab symmetric cloud model with spectral bin microphysics (the Hebrew University Cloud Model). The size distribution of sea spray particles (SSPs) at cloud base is calculated using the Lagrangian–Eulerian bin microphysics model. The model describes the SSP production, advection, and formation of the size distribution of SSP in the hurricane atmospheric boundary layer at different strong wind speeds. The SSP distributions calculated by the Lagrangian–Eulerian bin microphysics model are used in the parcel model and the Hebrew University Cloud Model to investigate the microphysical and dynamical effects of SSP on clouds. The SSPs ascending in cloud updrafts dramatically increase the number concentration of cloud drops within a wide range of drop sizes. As a result, sea spray creates clouds with unique property combinations of both maritime and continental types. These clouds have droplet size distributions characterized by a high drop concentration and a low effective radius, as in continental clouds. At the same time, the presence of SSP of a few hundred microns in radii triggers intense rain just above the cloud base, which is typical of extreme maritime clouds. In the presence of large sea spray drops, the smallest cloud condensational nuclei, including the smallest SSP, are activated, giving rise to the permanent in–cloud nucleation of small droplets, which produce a high concentration of small ice crystals above the level of homogeneous freezing. We showed that the SSP substantially increased the maximum vertical velocity, cloud water content, and mass contents of ice particles. Here, the results are compared with available observed data.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Microphysical and radiative characteristics of convective clouds during COHMEX
The microphysical structure and the evolution of two strong isolated thunderstorms that occurred on July 11, 1986 in northern Alabama were investigated using data obtained during the Cooperative Huntsville Meteorological Experiment by CP-2 multiparameter radar, together with passive microwave measurements from ER-2 aircraft. A correlation was found between the magnitude of the microwave T(B) depression and the storm intensity, although a clear relationship was not always obvious between radar-deduced microphysical characteristics and passive microwave radiative observations.
Fulton, Richard↗
High-resolution measurements of microphysics and entrainment in marine stratocumulus clouds
High-resolution measurements from the Airborne Cloud-Turbulence Observation System (ACTOS) during the Azores Stratocumulus Measurements of Radiation, Turbulence and Aerosols (ACORES) campaign are analysed for an investigation of the vertical profiles of microphysical properties and entrainment velocity ( W e ) in marine stratocumulus clouds. Here, the vertical profiles show the transition from the cloudy layer to free troposphere with nearly linear profiles of total water mixing ratio, liquid water potential temperature and virtual potential temperature, but the thickness of entrainment interfacial layer varies significantly. Sharp transitions of cloud microphysical and optical properties within a single horizontal flight leg are found in one stratocumulus cloud system. They seem to be related to the local environmental conditions, such as the wind shear and turbulent dissipation rate. W e values estimated by three methods show consistent tendencies in general and are clearly related to the local environmental conditions, such as vertical shear of the horizontal wind and turbulence intensity. However, the magnitudes of W e values differ by up to two orders of magnitude depending on the methods, which suggests that the estimation of W e from in situ measurements is still a challenge. Analysis of the microphysical response to entrainment suggests that inhomogeneous mixing occurs dominantly. On the other hand, the analysis results for the clouds under more humid conditions indicate a higher likelihood of homogeneous mixing.
54 ENVIRONMENTAL SCIENCES↗
Improving Representation of Convective Transport for Scale-Aware Parameterization – Part I: Convection and Cloud Properties Simulated with Spectral Bin and Bulk Microphysics
The ultimate goal of this study is to improve representation of convective transport by cumulus parameterization for meso-scale and climate models. As Part I of the study, we perform extensive evaluations of cloud-resolving simulations of a squall line and mesoscale convective complexes in mid-latitude continent and tropical regions using the Weather Research and Forecasting (WRF) model with spectral-bin microphysics (SBM) and with two double-moment bulk microphysics schemes: a modified Morrison (MOR) and Milbrandt and Yau (MY2). Compared to observations, in general, SBM gives better simulations of precipitation, vertical velocity of convective cores, and the vertically decreasing trend of radar reflectivity than MOR and MY2, and therefore will be used for analysis of scale-dependence of eddy transport in Part II. The common features of the simulations for all convective systems are (1) the model tends to overestimate convection intensity in the middle and upper troposphere, but SBM can alleviate much of the overestimation and reproduce the observed convection intensity well; (2) the model greatly overestimates radar reflectivity in convective cores (SBM predicts smaller radar reflectivity but does not remove the large overestimation); and (3) the model performs better for mid-latitude convective systems than tropical system. The modeled mass fluxes of the mid latitude systems are not sensitive to microphysics schemes, but are very sensitive for the tropical case indicating strong microphysics modification to convection. Cloud microphysical measurements of rain, snow and graupel in convective cores will be critically important to further elucidate issues within cloud microphysics schemes.
Fan, Jiwen↗
Optical and microphysical properties of a cold cirrus cloud - Evidence for regions of small ice particles
An airborne lidar and a scanning radiometer aboard an ER-2 aircraft were used to observe a cold cirrus cloud, and a Forward Scattering Spectrometer Probe (FSSP) was used to obtain simultaneous in situ microphysical observations at two altitudes within the cloud. Lidar depolarization ratio data show that the clouds were composed predominantly of ice crystals. At an altitude where the temperature was -62.7 C, the lidar and radiometer analysis gave a visible extinction to infrared absorption ratio (alpha) of 2.3, while the cloud microphysics data provided an alpha value of 3.77. The discrepancy is attributed to undersizing of particles by the FSSP. Direct and remote measurements showed better agreement for a lower layer where the temperature was -47.3 C.
Platt, C. M. R.↗
Assessing Clouds in GFDL's AM4.0 With Different Microphysical Parameterizations Using the Satellite Simulator Package COSP
We evaluate cloud simulations using satellite simulators against multiple observational data sets. These simulators have been run within the Geophysical Fluid Dynamics Laboratory's Atmosphere Model version 4.0 (AM4.0), as well as an alternative configuration where a fully two‐moment Morrison‐Gettelman cloud microphysical parameterization with prognostic precipitation (MG2) is applied, denoted as AM4‐MG2. The modeled cloud spatial distributions, vertical profiles, phase partitioning, cloud‐to‐precipitation transitions, and radiative effects compare reasonably well with satellite observations. Model biases include the under‐prediction of total and low‐level clouds, especially optically thin/intermediate clouds with cloud optical depth of less than 23, but the over‐prediction of thick clouds, indicating “too few, too bright” biases. These biases counteract each other, and give rise to reasonable estimates of cloud radiative effects. The underestimate of low‐level clouds is associated with too early and too frequent drizzle/precipitation formation. The precipitation bias is improved in AM4‐MG2, where the autoconversion scheme initiates the precipitation more realistically. There also exist discrepancies between models and observations for midlevel and high‐level clouds. Additional biases include the underestimate of liquid cloud fraction and the overestimate of ice cloud fraction.
54 ENVIRONMENTAL SCIENCES↗
Sensitivity of CAM5-simulated Arctic clouds and radiation to ice nucleation parameterization
Sensitivity of Arctic clouds and radiation in the Community Atmospheric Model, version 5, to the ice nucleation process is examined by testing a new physically based ice nucleation scheme that links the variation of ice nuclei (IN) number concentration to aerosol properties. The default scheme parameterizes the IN concentration simply as a function of ice supersaturation. The new scheme leads to a significant reduction in simulated IN concentration at all latitudes while changes in cloud amounts and properties are mainly seen at high- and midlatitude storm tracks. In the Arctic, there is a considerable increase in midlevel clouds and a decrease in low-level clouds, which result from the complex interaction among the cloud macrophysics, microphysics, and large-scale environment. The smaller IN concentrations result in an increase in liquid water path and a decrease in ice water path caused by the slowdown of the Bergeron–Findeisen process in mixed-phase clouds. Overall, there is an increase in the optical depth of Arctic clouds, which leads to a stronger cloud radiative forcing (net cooling) at the top of the atmosphere. The comparison with satellite data shows that the new scheme slightly improves low-level cloud simulations over most of the Arctic but produces too many midlevel clouds. Considerable improvements are seen in the simulated low-level clouds and their properties when compared with Arctic ground-based measurements. As a result, issues with the observations and the model–observation comparison in the Arctic region are discussed.
54 ENVIRONMENTAL SCIENCES↗