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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The role of local shipping emissions in aerosol-cloud interactions in the central Arctic

Arctic shipping is projected to increase as sea ice retreats, yet the impact of modern low-sulfur ship emissions on Arctic clouds and radiation remain poorly constrained. We use year-long in situ observations from the MOSAiC expedition to characterize ship-aerosol-cloud interactions for an icebreaker burning ultra-low sulfur fuel (0.1% mass per mass). Exhaust plumes were found to be strongly enriched in Aitken-mode particles, organic aerosol, and black carbon, but showed no detectable enhancement in particulate sulfate. Despite reduced hygroscopicity relative to ambient aerosols, ship emissions substantially increased local cloud condensation nuclei concentrations. A droplet activation parameterization was applied to quantify responses in cloud droplet number concentration ( N d ) to ship-induced perturbations in low-level Arctic clouds. In winter, abundant background accumulation-mode particles from Arctic haze supplied nearly all cloud droplets, while additional particles from ship emissions had little impact on N d . In contrast, during summer months, when unperturbed background aerosol concentrations are low, ship emissions nearly doubled N d compared to average background conditions and increased N d by a factor of five compared to very clean background conditions (25th percentile of background aerosol number concentrations). Longwave radiative transfer simulations for typical conditions of summer Arctic low-level clouds/fog suggest that these ship-induced increases in N d locally (i.e. <100 km downwind) lead to enhanced net surface longwave fluxes and consequent warming, primarily for optically thin clouds (liquid water path (LWP) ⩽ 30 g·m −2 ). For LWP = 10 g · m −2 , ship emissions lead to an increase of 1 W · m −2 in cloud longwave forcing at the surface compared to average unperturbed conditions (+7% relative increase), and up to 4 W · m −2 when compared to very clean background conditions (+22% relative increase). Even ultra-low sulfur fuel emissions can therefore locally and episodically modify Arctic cloud microphysics and radiative properties, especially during summer, implying that future increases in Arctic shipping could have non-negligible regional climate impacts.

Arctic↗
NASA NTRS2015

Investigation of the CCN Activity, BC and UVBC Mass Concentrations of Biomass Burning Aerosols during the 2013 BASELInE Campaign

Biomass-burning (BB) aerosols, acting as cloud condensation nuclei (CCN), can influence cloud microphysical and radiative properties. In this study, we present CCN measured near the BB source regions over northern Southeast Asia (Doi Ang Khang, Thailand) and at downwind receptor areas (Lulin Atmospheric Background Station, Taiwan), focusing exclusively on 13-20 March 2013 as part of 2013 spring campaign of the Seven SouthEast Asian Studies (7-SEAS) intensive observation. One of the campaigns objectives is to characterize BB aerosols serving as CCN in SouthEast Asia (SEA). CCN concentrations were measured by a CCN counter at 5 supersaturation (SS) levels: 0.15%, 0.30%, 0.45%, 0.60%, and 0.75%. In addition, PM2.5 and black carbon mass concentrations were analyzed by using a tapered element oscillating microbalance and an aethalometer. It was found the number-size distributions and the characteristics of hygroscopicity (e.g., activation ratio and k) of BB aerosols in SEA have a strong diurnal pattern, and different behaviors of patterns were characterized under two distinct weather systems. The overall average value was low (0.05-0.1) but comparable with previous CCN studies in other BB source regions. Furthermore, a large fraction of UV-absorbing organic material (UVBC) and high Delta-C among BB aerosols were also observed, which suggest the existence of substantial particulate organic matter in fresh BB aerosols. These data provide the most extensive characterization of BB aerosols in SEA until now.

biomass burning aerosol↗
DOE OSTI2024

NREL GOES Reference Document

The purpose of this document is to create a single reference document representing abridged versions of the PATMOS-x Algorithm Theoretical Basis Documents (ATBDs) specifically relevant to GOES 16-18 processing. This document has been compiled from several documents: Cloud Mask ATBD, AWG Cloud Height Algorithm (ACHA) ATBD, Daytime Cloud Optical and Microphysical Properties (DCOMP) ATBD, and CLAVR-x User's Guide.

14 SOLAR ENERGY↗
DOE OSTI2023

Particle inertial effects on radar Doppler spectra simulation

Abstract. Radar Doppler spectra observations provide a wealth of information about cloud and precipitation microphysics and dynamics. The interpretation of these measurements depends on our ability to simulate these observations accurately using a forward model. The effect of small-scale turbulence on the radar Doppler spectra shape has been traditionally treated by implementing the convolution process on the hydrometeor reflectivity spectrum and environmental turbulence. This approach assumes that all the particles in the radar sampling volume respond the same to turbulent-scale velocity fluctuations and neglects the particle inertial effect. Here, we investigate the inertial effects of liquid-phase particles on the forward modeled radar Doppler spectra. A physics-based simulation (PBS) is developed to demonstrate that big droplets, with large inertia, are unable to follow the rapid change of the velocity field in a turbulent environment. These findings are incorporated into a new radar Doppler spectra simulator. Comparison between the traditional and newly formulated radar Doppler spectra simulators indicates that the conventional simulator leads to an unrealistic broadening of the spectrum, especially in a strong turbulent environment. This study provides clear evidence to illustrate the droplet inertial effect on radar Doppler spectrum and develops a physics-based simulator framework to accurately emulate the Doppler spectrum for a given droplet size distribution (DSD) in a turbulence field. The proposed simulator has various potential applications for the cloud and precipitation studies, and it provides a valuable tool to decode the cloud microphysical and dynamical properties from Doppler radar observation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Cloud-generated radiative heating and its generation of available potential energy

The generation of zonal available potential energy (APE) by cloud radiative heating is discussed. The APE concept was mathematically formulated by Lorenz (1955) as a measure of the maximum amount of total potential energy that is available for conversion by adiabatic processes to kinetic energy. The rate of change of APE is the rate of the generation of APE minus the rate of conversion between potential and kinetic energy. By radiative transfer calculations, a mean cloud-generated radiative heating for a well defined set of cloud classes is derived as a function of cloud optical thickness. The formulation is suitable for using a general cloud parameter data set and has the advantage of taking into account nonlinearities between the microphysical and macrophysical cloud properties and the related radiation field.

Stuhlmann, R.↗
NASA NTRS1992

Sea ice-atmosphere interaction. Application of multispectral satellite data in polar surface energy flux estimates

Satellite data for the estimation of radiative and turbulent heat fluxes is becoming an increasingly important tool in large-scale studies of climate. One parameter needed in the estimation of these fluxes is surface temperature. To our knowledge, little effort has been directed to the retrieval of the sea ice surface temperature (IST) in the Arctic, an area where the first effects of a changing climate are expected to be seen. The reason is not one of methodology, but rather our limited knowledge of atmospheric temperature, humidity, and aerosol profiles, the microphysical properties of polar clouds, and the spectral characteristics of the wide variety of surface types found there. We have developed a means to correct for the atmospheric attenuation of satellite-measured clear sky brightness temperatures used in the retrieval of ice surface temperature from the split-window thermal channels of the advanced very high resolution radiometer (AVHRR) sensors on-board three of the NOAA series satellites. These corrections are specified for three different 'seasons' and as a function of satellite viewing angle, and are expected to be applicable to the perennial ice pack in the central Arctic Basin.

Steffen, Konrad↗
NASA NTRS1992

Galileo Probe Nephelometer Experiment

The objective of the Nephelometer Experiment aboard the Probe of the Galileo mission is to explore the vertical structure and microphysical properties of the clouds and hazes in the atmosphere of Jupiter along the descent trajectory of the Probe (nominally from 0.1 to greater than 10 bars). The measurements, to be obtained at least every kilometer of the Probe descent, will provide the bases for inferences of mean particle sizes, particle number densities (and hence, opacities, mass densities, and columnar mass loading) and, for nonhighly absorbing particles, for distinguishing between solid and liquid particles. These quantities, especially the location of the cloud bases, together with other quantities derived from this and other experiments aboard the Probe, will not only yield strong evidence for the composition of the particles, but, using thermochemical models, for species abundances as well. The measurements in the upper troposphere will provide 'ground truth' data for correlation with remote sensing instruments aboard the Galileo Orbiter vehicle.

Ragent, B.↗
NASA NTRS1993

Three dimensional modeling of cirrus during the 1991 FIRE IFO 2: Detailed process study

A three-dimensional model of cirrus cloud formation and evolution, including microphysical, dynamical, and radiative processes, was used to simulate cirrus observed in the FIRE Phase 2 Cirrus field program (13 Nov. - 7 Dec. 1991). Sulfate aerosols, solution drops, ice crystals, and water vapor are all treated as interactive elements in the model. Ice crystal size distributions are fully resolved based on calculations of homogeneous freezing of solution drops, growth by water vapor deposition, evaporation, aggregation, and vertical transport. Visible and infrared radiative fluxes, and radiative heating rates are calculated using the two-stream algorithm described by Toon et al. Wind velocities, diffusion coefficients, and temperatures were taken from the MAPS analyses and the MM4 mesoscale model simulations. Within the model, moisture is transported and converted to liquid or vapor by the microphysical processes. The simulated cloud bulk and microphysical properties are shown in detail for the Nov. 26 and Dec. 5 case studies. Comparisons with lidar, radar, and in situ data are used to determine how well the simulations reproduced the observed cirrus. The roles played by various processes in the model are described in detail. The potential modes of nucleation are evaluated, and the importance of small-scale variations in temperature and humidity are discussed. The importance of competing ice crystal growth mechanisms (water vapor deposition and aggregation) are evaluated based on model simulations. Finally, the importance of ice crystal shape for crystal growth and vertical transport of ice are discussed.

Jensen, Eric J.↗
NASA NTRS1993

SSH-2 measurements of cirrus at 18-28 micrometers from the King Air during FIRE 2

In November of 1991, the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) Phase II cirrus study took place at Coffeyville, Kansas. The field experiment incorporated instrumentation from surface, aircraft, and satellite to attempt to define the optical, radiative, and microphysical characteristics of these high altitude, predominantly ice clouds. The NCAR King Air research aircraft was outfitted with a variety of radiative and microphysical instrumentation for the FIRE II project. Included for this project was the SSH-2, a 16-channel passive radiometer. The SSH-2 was originally designed as a space-qualified infrared (IR) temperature and water vapor sounder for deployment onboard the Defense Meteorological Satellite Program (DMSP) series of environmental satellites. For this experiment, only those channels associated with the water vapor profiling function have been examined although downwelling radiance measurements were taken at all channels during the project. With supporting information from the aircraft telemetry observations it may be possible to relate these SSH-2 measurements to cloud radiative and microphysical properties. The following sections will describe the spectral characteristics of the instrument, the calibration scheme used to convert the raw measured counts into calibrated radiances, and the case studies that will be covered in this paper. This will be followed by a discussion of the results of this preliminary investigation and a description of future work to be done.

Griffin, Michael K.↗
NASA NTRS1994

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

One essential parameter used in the estimation of radiative and turbulent heat fluxes from satellite data is surface temperature. Sea and land surface temperature (SST and LST) retrieval algorithms that utilize the thermal infrared portion of the spectrum have been developed, with the degree of success dependent primarily upon the variability of the surface and atmospheric characteristics. However, little effort has been directed to the retrieval of the sea ice surface temperature (IST) in the Arctic and Antarctic pack ice or the ice sheet surface temperature over Antarctica and Greenland. The reason is not one of methodology, but rather our limited knowledge of atmospheric temperature, humidity, and aerosol vertical, spatial and temporal distributions, the microphysical properties of polar clouds, and the spectral characteristics of snow, ice, and water surfaces. Over the open ocean the surface is warm, dark, and relatively homogeneous. This makes SST retrieval, including cloud clearing, a fairly straightforward task. Over the ice, however, the surface within a single satellite pixel is likely to be highly heterogeneous, a mixture of ice of various thicknesses, open water, and snow cover in the case of sea ice. Additionally, the Arctic is cloudy - very cloudy - with typical cloud cover amounts ranging from 60-90 percent. There are few observations of cloud cover amounts over Antarctica. The goal of this research is to increase our knowledge of surface temperature patterns and magnitudes in both polar regions, by examining existing data and improving our ability to use satellite data as a monitoring tool. Four instruments are of interest in this study: the AVHRR, ATSR, SMMR, and SSM/I. Our objectives are as follows. Refine the existing AVHRR retrieval algorithm defined in Key and Haefliger (1992; hereafter KH92) and applied elsewhere. Develop a method for IST retrieval from ATSR data similar to the one used for SST. Further investigate the possibility of estimating surface temperature from passive microwave data (in conjunction with AVHRR clear sky samples) through the use of 'effective emissivities' and physical relationships between skin temperature and subsurface temperature. Use the general method outlined in MK93 to calculate a 12-year record of clear sky equivalent surface temperatures, or possibly all-sky snow-ice interface physical temperatures, from SMMR and SSM/I, compare these temperatures to climatologies, ECMWF modeled surface temperatures, and surface temperatures predicted by a 2-D ice model. And intercompare several ice surface retrieval methods and validate them against ground measurements from the Swiss Camp on the Greenland ice sheet. Additionally, we intend to develop a surface temperature product based on AVHRR data and possibly blended with drifting buoy and meteorological station temperatures.

Key, Jeff↗
NASA NTRS2002

Midlatitude Cirrus Clouds Derived from Hurricane Nora: A Case Study with Implications for Ice Crystal Nucleation and Shape

Hurricane Nora traveled up the Bala Peninsula coast in the unusually warm El Nino waters of September 1997, until rapidly decaying as it approached Southern California on 24 September. The anvil cirrus blowoff from the final surge of tropical convection became embedded in subtropical flow that advected the cirrus across the western US, where it was studied from the Facility for Atmospheric Remote Sensing (FARS) in Salt Lake City, Utah. A day later, the cirrus shield remnants were redirected southward by midlatitude circulations into the Southern Great Plains, providing a case study opportunity for the research aircraft and ground-based remote sensors assembled at the Clouds and Radiation Testbed (CART) site in northern Oklahoma. Using these comprehensive resources and new remote sensing cloud retrieval algorithms, the microphysical and radiative cloud properties of this unusual cirrus event are uniquely characterized. Importantly, at both the FARS and CART sites the cirrus generated spectacular optical displays, which acted as a tracer for the hurricane cirrus, despite the limited lifetimes of individual ice crystals. Lidar polarization data indicate widespread regions of uniform ice plate orientations, and in situ particle masticator data show a preponderance of pristine, solid hexagonal plates and columns. It is suggested that these unusual aspects are the result of the mode of cirrus particle nucleation, presumably involving the lofting of sea-salt nuclei in thunderstorm updrafts into the upper troposphere. This created a reservoir of haze particles that continued to produce halide-saltcontaminated ice crystals during the extended period of cirrus cloud maintenance. The reference that marine microliters are embedded in the replicas of ice crystals collected over the CART site points to the longevity of marine effects. Various nucleation scenarios proposed for cirrus clouds based on this and other studies, and the implications for understanding cirrus radiative properties or a global scale, are discussed.

Sassen, Kenneth↗
NASA NTRS2002

Meteorology, Macrophysics, Microphysics, Microwaves, and Mesoscale Modeling of Mediterranean Mountain Storms: The M8 Laboratory

Comprehensive understanding of the microphysical nature of Mediterranean storms can be accomplished by a combination of in situ meteorological data analysis and radar-passive microwave data analysis, effectively integrated with numerical modeling studies at various scales, from synoptic scale down through the mesoscale, the cloud macrophysical scale, and ultimately the cloud microphysical scale. The microphysical properties of and their controls on severe storms are intrinsically related to meteorological processes under which storms have evolved, processes which eventually select and control the dominant microphysical properties themselves. This involves intense convective development, stratiform decay, orographic lifting, and sloped frontal lifting processes, as well as the associated vertical motions and thermodynamical instabilities governing physical processes that affect details of the size distributions and fall rates of the various types of hydrometeors found within the storm environment. Insofar as hazardous Mediterranean storms, highlighted in this study by three mountain storms producing damaging floods in northern Italy between 1992 and 2000, developing a comprehensive microphysical interpretation requires an understanding of the multiple phases of storm evolution and the heterogeneous nature of precipitation fields within a storm domain. This involves convective development, stratiform transition and decay, orographic lifting, and sloped frontal lifting processes. This also involves vertical motions and thermodynamical instabilities governing physical processes that determine details of the liquid/ice water contents, size disi:ributions, and fall rates of the various modes of hydrometeors found within hazardous storm environments.

Starr, David O.↗
NASA NTRS2022

A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development.

machine learning/artificial intelligence↗
NASA NTRS2008

Optical-Microphysical Cirrus Model

A model is presented that permits the simulation of the optical properties of cirrus clouds as measured with depolarization Raman lidars. It comprises a one-dimensional cirrus model with explicit microphysics and an optical module that transforms the microphysical model output to cloud and particle optical properties. The optical model takes into account scattering by randomly oriented or horizontally aligned planar and columnar monocrystals and polycrystals. Key cloud properties such as the fraction of plate-like particles and the number of basic crystals per polycrystal are parameterized in terms of the ambient temperature, the nucleation temperature, or the mass of the particles. The optical-microphysical model is used to simulate the lidar measurement of a synoptically forced cirrostratus in a first case study. It turns out that a cirrus cloud consisting of only monocrystals in random orientation is too simple a model scenario to explain the observations. However, good agreement between simulation and observation is reached when the formation of polycrystals or the horizontal alignment of monocrystals is permitted. Moreover, the model results show that plate fraction and morphological complexity are best parameterized in terms of particle mass, or ambient temperature which indicates that the ambient conditions affect cirrus optical properties more than those during particle formation. Furthermore, the modeled profiles of particle shape and size are in excellent agreement with in situ and laboratory studies, i.e., (partly oriented) polycrystalline particles with mainly planar basic crystals in the cloud bottom layer, and monocrystals above, with the fraction of columns increasing and the shape and size of the particles changing from large thin plates and long columns to small, more isometric crystals from cloud center to top. The findings of this case study corroborate the microphysical interpretation of cirrus measurements with lidar as suggested previously.

Reichardt, J.↗
DOE OSTI2023

Maximum Supersaturation in the Marine Boundary Layer Clouds Over the North Atlantic

Abstract The maximum supersaturation ( S x ) in clouds is a key parameter affecting the cloud's microphysical and radiative properties. We investigate the S x of the marine boundary layer clouds by combining airborne and surface observations in the Eastern North Atlantic. The cloud droplet number concentration ( N c ) in the least diluted cloud cores agrees well with the number concentration of particles larger than the Hoppel Minimum (HM) ( N >HM ) below clouds, indicating that the HM represents the average size threshold above which particles are activated to form cloud droplets. The S x values derived from surface observations vary from 0.10% to 0.50% from June 2017 to June 2018, with a clear seasonal variation exhibiting higher values during winter. Most of the S x variance (∼60%) can be explained by the cloud condensation nuclei (CCN) concentration and updraft velocity ( w ), with the CCN concentration playing a more important role than w in explaining the variation of S x . The influence of CCN concentration on S x leads to a buffered response of N c to aerosol perturbations. The response of N c to low aerosol concentration during winter is further buffered by the high w . The global Community Earth System Model (CESM) simulated S x values in the Azores have a positive bias compared to measured S x , likely due to overestimated w and underestimated CCN concentration. The CESM simulated S x exhibits higher values further north over the North Atlantic Ocean, which is attributed to stronger w . The suppression of S x by aerosol is also evident in regions with high CCN concentrations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Investigating the Evolution of Ice Particle Distributions in Mixed-Phase Clouds

The goal of this project is to conduct modeling studies that focus on the processes that control the macrophysical and microphysical properties of mixed phase clouds, such as the partitioning of water phase and the processes that promote precipitation and govern cloud evolution. The process specific to this project is the collection of vapor-grown non-spherical ice crystals and snow hydrometeors through aggregation, as uncertainty remains in the evolution of particle properties as they aggregate. To aid in the understanding of ice particle evolution from pristine monomers to aggregates, the aggregation process is depicted using an offline simulator for ice crystal collection, namely the Ice Particle and Aggregate Simulator (IPAS). Of particular interest in the context of this work is the influence of monomer habit on aggregation and subsequently on cloud microphysical structure. This overarching goal has been completed by conducting modeling studies using the Adaptive Habit Model (AHM) in mixed-phase cloud systems, which predicts and evolves ice shape. While the AHM is designed with physical detail in mind, those details may be lost on larger spatial or temporal scales. Hence, how the contributions of particle growth and collection control the evolution of ice particle size distributions (PSDs) and redistribute mass within the cloud and at the surface has been investigated. Analyses include microphysical sensitivity investigations that inform on future improvement capabilities of microphysical parameterizations in larger scale models. Further, improvements of processes within ice clouds have resulted from this work as the environmental processes controlling ice crystal growth, microphysical processes, and precipitation are inherently integrated within this investigation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1983

The clouds are hazes of Venus

Pioneer Venus and Venera probe data for the clouds of Venus are considered. These clouds consist of a main cloud deck at 45-70 km altitude, with thinner hazes above and below, although the microphysical properties of the main cloud are further subdivided into upper, middle and lower cloud levels. Much of the cloud exhibits a multimodal particle size distribution, with the mode most visible from the earth being H2SO4 droplets having 2-3 micron diameters. Despite variations, the vertical structure of the clouds indicates persistent features at sites separated by years and by great distances. The clouds are more strongly affected by radiation than by latent heat release, and the small particle size and weak convective activity observed are incompatible with lightning of cloud origin.

Esposito, L. W.↗
NASA NTRS2005

Cloud Properties Simulated by a Single-Column Model. Part II: Evaluation of Cumulus Detrainment and Ice-phase Microphysics Using a Cloud Resolving Model

This paper is the second in a series in which kilometer-scale-resolving observations from the Atmospheric Radiation Measurement program and a cloud-resolving model (CRM) are used to evaluate the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model. Part I demonstrated that kilometer-scale cirrus properties simulated by the SCM significantly differ from the cloud radar observations while the CRM simulation reproduced most of the cirrus properties as revealed by the observations. The present study describes an evaluation, through a comparison with the CRM, of the SCM's representation of detrainment from deep cumulus and ice-phase microphysics in an effort to better understand the findings of Part I. It is found that detrainment occurs too infrequently at a single level at a time in the SCM, although the detrainment rate averaged over the entire simulation period is somewhat comparable to that of the CRM simulation. Relatively too much detrained ice is sublimated when first detrained. Snow falls over too deep of a layer due to the assumption that snow source and sink terms exactly balance within one time step in the SCM. These characteristics in the SCM parameterizations may explain many of the differences in the cirrus properties between the SCM and the observations (or between the SCM and the CRM). A possible improvement for the SCM consists of the inclusion of multiple cumulus cloud types as in the original Arakawa-Schubert scheme, prognostically determining the stratiform cloud fraction and snow mixing ratio. This would allow better representation of the detrainment from deep convection, better coupling of the volume of detrained air with cloud fraction, and better representation of snow field.

Luo, Yali↗