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NASA NTRS1993

Effect of Amazon smoke on cloud microphysics and albedo - Analysis from satellite imagery

The effect of smoke aerosol particles on the properties of low cumulus and stratocumulus clouds is studied on the basis of NOAA AVHRR images taken over the Brazilian Amazon Basin during the biomass burning season of 1987. The reflectance at a wavelength of 0.64 micron and the drop size, derived from the cloud reflectance at 3.75 microns, is studied for tens of thousands of clouds. It is shown that the presence of dense smoke can reduce the remotely sensed drop size of continental cloud drops from 15 to 9 microns. Due to both the high initial reflectance of clouds in the visible part of the spectrum and the presence of graphitic carbon, the average cloud reflectance at 0.6 micron is reduced from 0.71 to 0.68 for an increase in smoke optical thickness from 0.1 to 2.0. High concentration of aerosol particles is shown to cause a decrease in the cloud-drop size, and smoke is found to darken the bright Amazonian clouds.

Kaufman, Yoram J.↗

NASA NTRS1989

Dust clouds in Orion and the interstellar neutral hydrogen distribution

According to published examples of the far IR observations in the Orion and its surroundings, several well defined dust clouds of different sizes and structure are present. For comparison of these clouds with the neutral hydrogen distribution on the area of approx. 1000 sq degs, the data from Pulkovo Sky Survey in the interstellar neutral Hydrogen Radio Line as well as special observations with the RATAN-600 telescope in 21 cm line were used. From the materials of Pulkovo HI Survey, the data were taken near the line emission at ten velocities between -21.8 and +25.6 km/s LSR for the structural component of the interstellar hydrogen emission. The results given concern mainly the Orion's Great Dust Cloud and the Lambda Orionis region where the information about the situation with the dust and interstellar hydrogen is very essential for interpretation.

Bystrova, N. V.↗

NASA NTRS2016

Performance of the Goddard Multiscale Modeling Framework with Goddard Ice Microphysical Schemes

The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has become a new approach for climate modeling. The embedded CRMs make it possible to apply CRM-based cloud microphysics directly within a GCM. However, most such schemes have never been tested in a global environment for long-term climate simulation. The benefits of using an MMF to evaluate rigorously and improve microphysics schemes are here demonstrated. Four one-moment microphysical schemes are implemented into the Goddard MMF and their results validated against three CloudSat/CALIPSO cloud ice products and other satellite data. The new four-class (cloud ice, snow, graupel, and frozen drops/hail) ice scheme produces a better overall spatial distribution of cloud ice amount, total cloud fractions, net radiation, and total cloud radiative forcing than earlier three-class ice schemes, with biases within the observational uncertainties. Sensitivity experiments are conducted to examine the impact of recently upgraded microphysical processes on global hydrometeor distributions. Five processes dominate the global distributions of cloud ice and snow amount in long-term simulations: (1) allowing for ice supersaturation in the saturation adjustment, (2) three additional correction terms in the depositional growth of cloud ice to snow, (3) accounting for cloud ice fall speeds, (4) limiting cloud ice particle size, and (5) new size-mapping schemes for snow and graupel. Despite the cloud microphysics improvements, systematic errors associated with subgrid processes, cyclic lateral boundaries in the embedded CRMs, and momentum transport remain and will require future improvement.

snow↗

NASA NTRS1974

Infrared maser emission from interstellar hydroxyl molecules

The energy structure and transition rates of the OH radical were studied in rotational and vibrational energies to provide the basis for studies of the population distributions under various exciting mechanisms. The absorption of ultra-violet or near infrared radiation which might explain the microwave emission was examined, as well as the absorption of low temperature blackbody radiation and collisions with molecular hydrogen. The results of the population studies were applied to the transfer equation, and a model of a uniform spherical cloud of OH was used with the pumping process which occurs uniformly throughout the region. The emission is unsaturated and the intensity is an exponential function of the size of the cloud for high pumping rates, and the region of unsaturated emission shrinks for lower pumping rates until the entire region is saturated, the intensity then becoming a linear function of the size of the emitting cloud.

Pelzmann, R. F., Jr.↗

NASA NTRS2005

Evolution of a Florida Cirrus Anvil

This paper presents a detailed study of a single thunderstorm anvil cirrus cloud measured on 21 July 2002 near southern Florida during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers--Florida Area Cirrus Experiment (CRYSTAL-FACE). NASA WB-57F and University of North Dakota Citation aircraft tracked the microphysical and radiative development of the anvil for 3 h. Measurements showed that the cloud mass that was advected downwind from the thunderstorm was separated vertically into two layers: a cirrus anvil with cloud-top temperatures of -45?C lay below a second, thin tropopause cirrus (TTC) layer with the same horizontal dimensions as the anvil and temperatures near -70?C. In both cloud layers, ice crystals smaller than 50 ?m across dominated the size distributions and cloud radiative properties. In the anvil, ice crystals larger than 50 ?m aggregated and precipitated while small ice crystals increasingly dominated the size distributions; as a consequence, measured ice water contents and ice crystal effective radii decreased with time. Meanwhile, the anvil thinned vertically and maintained a stratification similar to its environment. Because effective radii were small, radiative heating and cooling were concentrated in layers approximately 100 m thick at the anvil top and base. A simple analysis suggests that the anvil cirrus spread laterally because mixing in these radiatively driven layers created horizontal pressure gradients between the cloud and its stratified environment. The TTC layer also spread but, unlike the anvil, did not dissipate--perhaps because the anvil shielded the TTC from terrestrial infrared heating. Calculations of top-of-troposphere radiative forcing above the anvil and TTC showed strong cooling that tapered as the anvil evolved.

Garrett, T. J.↗

NASA NTRS1989

Theory of droplet. Part 1: Renormalized laws of droplet vaporization in non-dilute sprays

The vaporization of a droplet, interacting with its neighbors in a non-dilute spray environment is examined as well as a vaporization scaling law established on the basis of a recently developed theory of renormalized droplet. The interacting droplet consists of a centrally located droplet and its vapor bubble which is surrounded by a cloud of droplets. The distribution of the droplets and the size of the cloud are characterized by a pair-distribution function. The vaporization of a droplet is retarded by the collective thermal quenching, the vapor concentration accumulated in the outer sphere, and by the limited percolative passages for mass, momentum and energy fluxes. The retardation is scaled by the local collective interaction parameters (group combustion number of renormalized droplet, droplet spacing, renormalization number and local ambient conditions). The numerical results of a selected case study reveal that the vaporization correction factor falls from unity monotonically as the group combustion number increases, and saturation is likely to occur when the group combustion number reaches 35 to 40 with interdroplet spacing of 7.5 diameters and an environment temperature of 500 K. The scaling law suggests that dense sprays can be classified into: (1) a diffusively dense cloud characterized by uniform thermal quenching in the cloud; (2) a stratified dense cloud characterized by a radial stratification in temperature by the differential thermal quenching of the cloud; or (3) a sharply dense cloud marked by fine structure in the quasi-droplet cloud and the corresponding variation in the correction factor due to the variation in the topological structure of the cloud characterized by a pair-distribution function of quasi-droplets.

Chiu, H. H.↗

NASA NTRS2002

Impact of MIE-Resonances on the Atmospheric Absorption of Water Clouds

Clouds strongly modulate radiative transfer processes in the Earth's atmosphere. Studies, which simulate bulk properties of clouds, such as absorption, require methods that accurately account for multiple scattering among individual cloud particles. Multiple scattering processes are well described by MIE-theory, if interacting particles have a spherical shape. This is a good assumption for water droplets. Thus, simulations for water clouds (especially for interactions with solar radiation) usually apply readily available MIE-codes. The presence of different drop-sizes, however, necessitates repetitive calculations for many sizes. The usual representation by a few sizes is likely to miss contributions from densely distributed, sharp resonances. Despite their usually narrow width, integrated over the entire size-spectrum of a cloud droplet distribution, the impact of missed resonances could add up. The consideration of these resonances tends to increase cloud extinction and cloud absorption. This mechanism for a larger (than by MIE-methods predicted) solar absorption has the potential to explain observational evidence of larger than predicted cloud absorption at solar wavelengths. The presentation will address the absorption impact of added resonances for typical properties of water clouds (e.g. drop size distributions, drop concentrations and cloud geometry). Special attention will be given to scenarios with observational evidence of law than simulated solar absorption; particularly if simultaneous measurements of cloud micro- and macrophysical properties are available.

Wiscombe, W.↗

NASA NTRSDate not supplied

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided many statistics on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus was segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution possible for capturing cloud initiation and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool, strategies to identify development stages from cloud tracks, and preliminary results that document cumulus lifecycle properties from satellite. The application of AHI 0.5-km reflectance has both strengths and limitations when attempting to track lifecycles of the smallest resolvable clouds. We show that by aggregating cloud tracks from a few case studies of CAMP2EX, we can discern differences in cloud lifetime and development according to ensembles selected from areas of interest. The results demonstrate an ability to quantify lifetimes and assess rates of change in cloud characteristics that are likely controlled by the surrounding environment and meteorology.

Cloud Tracking↗

NASA NTRSDate not supplied

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided valuable insight on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus were segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution available for capturing cloud initiation, growth, and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool and its results for cloud fields sampled throughout CAMP2EX by the airborne P-3. Cloud tracks were selected from about 10 flights to form ensembles, specific groups of tracks occurring in a region with airborne sampling. Cloud lifecycle properties, including duration and maximum area, are calculated for all ensemble members, and analyzed for cloud behavior and P-3 coincidences. By following this strategy, we quantitatively assess the degree of airborne sampling for specific cloud classes defined by the lifecycle calculations. We can summarize which cloud classes had more sampling, the stage of development during sampling, and general differences in character (e.g., isolated congestus vs. cold-pool producer).

Cloud Tracking↗

NASA NTRS2022

LGM Paleoclimate Constraints Inform Cloud Parameterizations and Equilibrium Climate Sensitivity in CESM2

The Community Earth System Model version 2 (CESM2) simulates a high equilibrium climate sensitivity (ECS > 5°C) and a Last Glacial Maximum (LGM) that is substantially colder than proxy temperatures. In this study, we examine the role of cloud parameterizations in simulating the LGM cooling in CESM2. Through substituting different versions of cloud schemes in the atmosphere model, we attribute the excessive LGM cooling to the new CESM2 schemes of cloud microphysics and ice nucleation. Further exploration suggests that removing an inappropriate limiter on cloud ice number (NoNimax) and decreasing the time-step size (substepping) in cloud microphysics largely eliminate the excessive LGM cooling. NoNimax produces a more physically consistent treatment of mixed-phase clouds, which leads to an increase in cloud ice content and a weaker shortwave cloud feedback over mid-to-high latitudes and the Southern Hemisphere subtropics. Microphysical substepping further weakens the shortwave cloud feedback. Based on NoNimax and microphysical substepping, we have developed a paleoclimate-calibrated CESM2 (PaleoCalibr), which simulates well the observed twentieth century warming and spatial characteristics of key cloud and climate variables. PaleoCalibr has a lower ECS (∼4°C) and a 20% weaker aerosol-cloud interaction than CESM2. PaleoCalibr represents a physically more consistent treatment of cloud microphysics than CESM2 and is a valuable tool in climate change studies, especially when a large climate forcing is involved. Our study highlights the unique value of paleoclimate constraints in informing the cloud parameterizations and ultimately the future climate projection.

equilibrium climate sensitivity↗

DOE OSTI2020

Size dependence in chord characteristics from simulated and observed continental shallow cumulus

Abstract. In this study we compare long-term Doppler and Raman lidar observations against a full month of large eddy simulations of continental shallow cumulus clouds. The goal is to evaluate if the simulations can reproduce the mean observed vertical velocity and moisture structure of cumulus clouds and their associated subcloud circulations, as well as to establish if these properties depend on the size of the cloud. We propose methods to compare continuous chords of cloud detected from Doppler and Raman lidars with equivalent chords derived from 1D and 3D model output. While the individual chords are highly variable, composites of thousands of observed and millions of simulated chords contain a clear signal. We find that the simulations underestimate cloud size and fraction but successfully reproduce the observed structure of vertical velocity and moisture perturbations. There is a clear scaling of vertical velocity and moisture anomalies below the chords with chord size, but the moisture anomalies are only 1 %–2 % higher than the horizontal mean values. The differences between the observations and simulations are smaller than the difference in sampling the modeled chords in time or space. The shape of the vertical velocity and moisture anomalies from cloud chords sampled spatially from 3D model snapshots is almost perfectly symmetric. In contrast, the chords sampled temporally from the lidar observations and 1D model output have a marked asymmetry, with stronger updrafts and higher moisture anomalies occurring earlier on.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

RSP Data Status, Updates and Plans from the Team

•All radiance (L1C), aerosol and cloud (L2) products are in the archive. •Revised calibration performed at GSFC in July 2021 applied to reprocessing. •Clouds have smaller drops and higher optical depths (larger droplet number concentrations) in winter than in summer. Cloud top droplet size distributions tend to be narrow with roughly 80% having an effective variance of less than 0.07. This is relevant to how well bulk auto-conversion parameterizations are likely to work at cloud top (order of magnitude effects) and also to assumptions used in the remote sensing of droplet number (~ 10% effect). Real refractive index and effective radius retrievals are consistent with hygroscopic growth of aerosols Real refractive index and effective variance retrievals imply the presence of an insoluble fraction of aerosols Future work on clouds will look at differences in cloud top drizzle formation and auto-conversion rates between the different campaigns and at how well mixed phase clouds can be detected (if at all) from sensors such as VIIRS and PACE OCI.

Research Scanning Polarimeter↗

DOE OSTI2020

Rapid growth of anthropogenic organic nanoparticles greatly alters cloud lifecycle in the Amazon rainforest

Atmospheric nanoparticles can significantly influence Earth’s climate if they grow to sizes large enough to nucleate cloud droplets. While the contribution of extremely low volatility vapors to nanoparticle growth has been discussed extensively, the role of semivolatile organics has been largely overlooked. Here we examine the growth and impacts of air pollution nanoparticles from an isolated metropolis amidst the Amazon rainforest. Although extremely low volatility organics are necessary for the initial growth of nanoparticles, model analysis suggests that dynamic gas-particle partitioning of semivolatile oxidation products of anthropogenic and natural hydrocarbons is predominantly responsible for the observed rapid growth to 50 nm. Furthermore, cloud-resolving simulations demonstrate that the grown particles appreciably modify shallow cloud droplet size distribution, suppress precipitation, and enhance the transition to deep clouds. With condensable semivolatile organics typically formed in greater proportion, similar nanoparticle growth and impacts on clouds could likely occur in heavily urbanized forested regions globally.

Zaveri, Rahul A↗

DOE OSTI2020

DATASET: Rapid growth of anthropogenic organic nanoparticles greatly alters cloud lifecycle in the Amazon rainforest

Zaveri, Rahul A↗

DOE OSTI2024

Reduced‐Order Modeling for Linearized Representations of Microphysical Process Rates

Abstract Representing cloud microphysical processes in large scale atmospheric models is challenging because many processes depend on the details of the droplet size distribution (DSD, the spectrum of droplets with different sizes in a cloud). While full or partial statistical moments of droplet size distributions are the typical variables used in bulk models, prognostic moments are limited in their ability to represent microphysical processes across the range of conditions experienced in the atmosphere. Microphysical parameterizations employing prognostic moments are known to suffer from structural uncertainty in their representations of inherently higher dimensional cloud processes, which limit model fidelity and lead to forecasting errors. Here we investigate how data‐driven reduced‐order modeling can be used to learn predictors for microphysical process rates in bulk microphysics schemes in an unsupervised manner from higher dimensional bin distributions. Using simulations characteristic of marine stratiform clouds, we simultaneously learn lower dimensional representations of droplet size distributions and predict the evolution of the microphysical state of the system. Droplet collision‐coalescence, the main process for generating warm rain, is estimated to have an intrinsic dimension of three. This intrinsic dimension provides a lower limit on the number of degrees of freedom needed to accurately represent collision‐coalescence in models. We demonstrate how deep learning based reduced‐order modeling can be used to discover intrinsic coordinates describing the microphysical state of the system, where process rates such as collision‐coalescence are globally linearized. These implicitly learned representations of the DSD retain more information about the DSD than typical moment‐based representations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1993

Cloud clusters and superclusters over the oceanic warm pool

A study aimed at examining the size distributions of cloud clusters and the temperature distributions within them as functions of location, year, phase of the ISV, and time of day is considered. IR satellite images of tropical convection over the oceanic warm pool were processed to reveal cloud clusters, connected areas with cloud-top temperatures lower than a given threshold value. Results were obtained for a very cold threshold (208 K), corresponding roughly to the radar echo area within Australian monsoon cloud clusters, and for a moderately cold threshold (235 K) frequently used in climatic rainfall estimation.

Mapes, Brian E.↗

NASA NTRS2003

Radar Reflectivity Simulated by a 2-D Spectra Bin Model: Sensitivity of Cloud-aerosol Interaction

The Goddard Cumulus Ensemble (GCE) model with bin spectra microphysics is used to simulate mesoscale convective systems.The model uses explicit bins to represent size spectra of cloud nuclei, water drops, ice crystals, snow and graupel. Each hydrometeorite category is described by 33 mass bins. The simulations provide a unique data set of simulated raindrop size distribution in a realistic dynamic frame. Calculations of radar parameters using simulated drop size distribution serve as an evaluation of numerical model performance. In addition, the GCE bin spectra modes is a very useful tool to study uncertainties related to radar observations; all the environmental parameters are precisely known. In this presentation, we concentrate on the discussion of Z-R (ZDR-R) relation in the simulated systems. Due to computational limitations, the spectra bin model has been run in two dimensions with 31 stretched vertical layers and 1026 horizontal grid points (1 km resolution). Two different cases, one in midlatitude continent, the other in tropical ocean, have been simulated. The continental case is a strong convection which lasted for two hours. The oceanic case is a persistent system with more than 10 hours' life span. It is shown that the simulated Z-R (ZDR-R) relations generally agree with observations using radar and rain gauge data. The spatial and temporal variations of Z-R relation in different locations are also analyzed. Impact of aerosols on cloud formation and raindrop size distribution was studied. Both clean (low CCN) and dirty (high CCN) cases are simulated. The Z-R relation is shown to vary considerable in the initial CCN concentrations.

Li, Kiaowen↗

NASA NTRS1979

Studies on remote sensing method of particle size and water density distribution in mists and clouds using laser radar techniques

A method of remote measurement of the particle size and density distribution of water droplets was developed. In this method, the size of droplets is measured from the Mie scattering parameter which is defined as the total-to-backscattering ratio of the laser beam. The water density distribution is obtained by a combination of the Mie scattering parameter and the extinction coefficient of the laser beam. This method was examined experimentally for the mist generated by an ultrasonic mist generator and applied to clouds containing rain and snow. Compared with the conventional sampling method, the present method has advantages of remote measurement capability and improvement in accuracy.

Shimizu, H.↗