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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.

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At least 253 records · Page 14

Expanding SPoRT RGBs and Machine Learning Techniques to Enhance Air Quality Monitoring in Southern Asia

Air pollution poses significant environmental, public health, and societal concerns in the Hindu Kush Himalaya (HKH) region of south-central Asia, notably during the dry monsoon months (~November to May). Key contributors to poor air quality include dust from the Middle East and western India, persistent nocturnal fog/smog, and biomass burning. To address this issue, we established a robust air quality and chemistry observation and modeling product suite utilizing multi-spectral red-green-blue (RGB) composite satellite products from Korea’s GEO-KOMPSAT-2A satellite, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model for dust transport forecasts, and the Weather Research and Forecasting coupled with Chemistry (WRF-Chem) model to predict aerosols and chemical species concentrations. Our team employed similar RGB recipes transitioned by the NASA Short-term Prediction Research and Transition (SPoRT) Center for the GOES-R era products over the Western Hemisphere, with significant success in depicting dust and nocturnal fog / low clouds, and to a lesser extent smoke and fire hot spots. We will extend these capabilities for the HKH region by applying an artificial intelligence (AI) model that objectively identifies dust from multi-spectral satellite data over the Southwestern United States. The AI model will be calibrated for automated dust detection over HKH from GEO-KOMPSAT-2A satellite data, with a goal of developing a similar AI model for objectively identifying smoke as well. The ultimate goal of this effort is to enhance dust and smoke predictions in the region by establishing improved emission initializations in HYSPLIT and/or WRF-Chem through the automated AI detection of dust and smoke.

Jonathan L. Case↗

The Amazon River‐Breeze Circulation Limits Detection of Aerosol‐Cloud Interactions in Warm Clouds

Increased aerosol concentrations can brighten low-level clouds and extend their lifetimes, but aerosol–cloud interactions (ACI) remain highly uncertain and difficult to quantify. We show that part of this uncertainty is caused by topographical influences on clouds, that is, those arising from land–water contrasts. This is demonstrated using satellite retrievals in regions with extensive river networks, such as the Amazon Basin. 15 years of MODerate resolution Imaging Spectroradiometer (MODIS) satellite data show cloud formation over the Amazon River basin is suppressed by 26% with warm low clouds above the river exhibiting a 22% smaller droplet effective radius and 18% higher droplet concentration ($N_d$) compared to adjacent land clouds. Thus, clouds above the river may appear polluted but are actually influenced by river-breeze circulations driven by the thermal contrast between the river and the surrounding land. These responses are robust in both wet and dry seasons, and tests using an improved MODIS retrieval product show cloud differences are unlikely due to retrieval artifacts. In situ measurements from the Green Ocean Amazon Experiment (GoAmazon) confirm that $N_d$ is elevated above rivers and are also higher when carbon monoxide concentrations are elevated near the large city of Manaus. Lagrangian airmass tracking over Manaus shows that regional-scale river-breeze circulations impact $N_d$ as much as the urban aerosol plume, complicating ACI attribution and highlighting the need to isolate land-surface effects to assess ACI in continental regions.

Aerosol-Cloud Interactions↗

The dynamics of low-beta plasma clouds as simulated by a three-dimensional, electromagnetic particle code

A 3D electromagnetic and relativistic particle simulation code is used to investigate the dynamics of low-beta plasma clouds moving perpendicular to an ambient magnetic field in vacuum and in a background plasma. The simulations show the formation of the space charge sheaths at the sides of the cloud with the associated polarization electric field which facilitate the cross-field propagation, as well as the sheaths at the front and rear end of the cloud caused by the larger ion Larmor radius, which allows ions to move ahead and lag behind the electrons as they gyrate. It is found that, in a background plasma, electron and ion sheaths expand along the magnetic field at the same rate, whereas in vacuum the electron sheath expands much faster than the ion sheath. Sheath clouds are accelerated up to relativistic energies, which indicates that artificial plasma clouds released in the ionosphere or magnetosphere may generate optical emissions as energetic sheath electrons scatter in the upper atmosphere.

Neubert, T.↗

Cloud Condensation Nuclei in FIRE III

Yum and Hudson showed that the springtime Arctic aerosol is probably a result of long-range transport at high altitudes. Scavenging of particles by clouds reduces the low level concentrations by a factor of 3. This produces a vertical gradient in particle concentrations when low-level clouds are present. Concentrations are uniform with height when clouds are not present. Low-level CCN (cloud condensation nuclei) spectra are similar to those in other maritime areas as found by previous projects including FIRE 1 and ASTEX, which were also supported on earlier NASA-FIRE grants. Wylie and Hudson carried this work much further by comparing the CCN spectra observed during ACE with back trajectories of air masses and satellite photographs. This showed that cloud scavenging reduces CCN concentrations at all altitudes over the springtime Arctic, with liquid clouds being more efficient scavengers than frozen clouds. The small size of the Arctic Ocean seems to make it more susceptible to continental and thus anthropogenic aerosol influences than any of the other larger oceans.

Hudson, James G.↗

RACORO Continental Boundary Layer Cloud Investigations: 3. Separation of Parameterization Biases in Single-Column Model CAM5 Simulations of Shallow Cumulus

Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) Project has constructed case studies from the Atmospheric Radiation Measurement Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only a relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.

parameterization↗

Spitzer Spectroscopy of Low-Mass Dwarfs - Clouds and Chemistry at the Bottom of the IMF

Brown dwarfs and low-mass stars show evidence of complicated atmospheres, including a variety of molecular species and clouds. Infrared observations are one of the best probes of the physics of these objects, but up until recently these observations have been limited in studies from ground-based telescopes by atmospheric absorption and insufficient sensitivity. With the launch of the Spitzer Space Telescope with its Infrared Spectrograph (IRS) instrument we now have the capability to undertake a systematic study of the atmospheric structure and chemistry in these cool objects. The IRS Dim Suns team has compiled spectra from objects ranging from M1 dwarfs with effective temperatures 3,800K of down to T8 dwarfs with effective temperatures of 700. This talk will present these results and discuss their implications for our understanding of cool dwarf atmospheric physics and structure.

Roellig, Thomas L.↗

Low Pressure Experimental Simulation of Electrical Discharges Above and Inside a Cloud

A low pressure laboratory experiment to generate sporadic electrical discharges in either a particulate dielectric or air, representing a competing path of preferred electrical breakdown, was investigated. At high pressures, discharges occurred inside the dielectric particulate; at low pressures, discharges occurred outside the dielectric particulate; at a transition pressure regime, which depends on conductivity of the dielectric particulate, discharges were simultaneously generated in both particulate dielectric and air. Unique use of a particulate dielectric was critical for sporadic discharges at lower pressures which were not identical in character to discharges without the particulate dielectric. Application of these experimental results to the field of atmospheric electricity and simulation of the above-cloud type discharges that have recently been documented, called jets and sprites, are discussed.

Jarzembski, Maurice A.↗

Spectral Dependence of MODIS Cloud Droplet Effective Radius Retrievals for Marine Boundary Layer Clouds

Low-level warm marine boundary layer (MBL) clouds cover large regions of Earth's surface. They have a significant role in Earth's radiative energy balance and hydrological cycle. Despite the fundamental role of low-level warm water clouds in climate, our understanding of these clouds is still limited. In particular, connections between their properties (e.g. cloud fraction, cloud water path, and cloud droplet size) and environmental factors such as aerosol loading and meteorological conditions continue to be uncertain or unknown. Modeling these clouds in climate models remains a challenging problem. As a result, the influence of aerosols on these clouds in the past and future, and the potential impacts of these clouds on global warming remain open questions leading to substantial uncertainty in climate projections. To improve our understanding of these clouds, we need continuous observations of cloud properties on both a global scale and over a long enough timescale for climate studies. At present, satellite-based remote sensing is the only means of providing such observations.

Cloud physics↗

Observational Constraint on Cloud Feedbacks Suggests Moderate Climate Sensitivity

Global climate models (GCMs) predict warming in response to increasing greenhouse gases, partly due to decreased tropical low-level cloud cover and reflectance. We use satellite observations that discriminate stratocumulus (Sc) from shallow cumulus (Cu) clouds to separately evaluate their sensitivity to warming and constrain the tropical contribution to low-cloud feedback. We find an observationally inferred low-level feedback two times smaller than a previous estimate. Cu are insensitive to warming whereas GCMs exhibit a large positive cloud feedback in Cu regions. In contrast, Sc show sensitivity to warming and the tropical inversion layer strength, controlled by the tropical Pacific SST gradient. Models fail to reproduce the historical SST gradient trends and therefore changes in inversion strength, generating an overestimate of the positive Sc cloud feedback. Continued weak east-Pacific warming would therefore produce a weaker low-cloud feedback and imply a more moderate climate sensitivity (3.47  0.33 K) than many models predict.

Cloud feedback↗

Towards a More Realistic Representation of NASA CERES-derived Surface Radiative Fluxes during Polar Night: A Comparison with the MOSAiC Field Campaign

The Arctic remains one of the more difficult regions observe, and so satellite observations are a critical tool for observing the region, such as those from Clouds and the Earth’s Radiant Energy System (CERES). But validating the satellite surface radiative flux estimates is difficult because of the lack of in situ measurements. The extensive high-quality surface radiative flux and meteorological measurements collected from MOSAiC provide a useful check on flux retrievals from CERES instruments. We compare MOSAiC and CERES surface radiative fluxes during October through March of 2019-2020 using the large set of meteorological measurements also collected by MOSAiC, specifically cloud properties. Previous work identified a significant source of error in the CERES estimate of surface downwelling longwave flux as the estimate of low level cloud amount when compared with MOSAiC W-band radar measurements. Continuing this work, we examine the effects of errors in cloud water path on surface radiative fluxes. When using all cloud conditions, errors in cloud water are also significantly correlated with surface radiative flux errors, though the size off the effect is only about half that of cloud amount. But when considering low cloud conditions only, the effects of cloud water and cloud amount are comparable. We compare MOSAiC and CERES surface radiative fluxes during October through March of 2019-2020 using the large set of meteorological measurements also collected by MOSAiC, specifically cloud properties. Previous work identified a significant source of error in the CERES estimate of surface downwelling longwave flux as the estimate of low level cloud amount when compared with MOSAiC W-band radar measurements. We further examine this source of error by examining selected case studies in which the disagreements in radiative fluxes and clouds are large.

J Brant Dodson↗

Diagnosing convective instability using VAS data

The utility of combining visible and various infrared images from the VAS to produce a forecasting tool, that can be available on a near real time basis, to predict severe weather development is shown. Areas where dry air in the midtroposphere overlays substantial moisture at low levels are used to diagnose mesoscale regions that have the potential for being convectively unstable before the onset of severe convection. Specifically, 6.7 micron water vapor imagery, used for isolating regions of substantial midlevel dryness, are combined with images of low level clouds or with split-window low level moisture images to delineate regions that have the potential for convective instability. In areas where scattered low level clouds are present, computer generated, color image combinations are used to isolate those warm, low level clouds that are in potential convectively unstable environments from clouds that exist under a deeply moist atmosphere. In clear regions, the split window technique is used for delineating areas of substantial boundary layer moisture. These images are again computer overlayed by the midlevel dryness to produce a color coded image of potential convective instability.

Petersen, R. A.↗

Towards A More Realistic Representation of Nasa Ceres-Derived Surface Radiative Fluxes During Polar Night: A Comparison With the Mosaic Field Campaign

The Arctic remains one of the more difficult regions observe, and so satellite observations are a critical tool for observing the region, such as those from Clouds and the Earth’s Radiant Energy System (CERES). But validating the satellite surface radiative flux estimates is difficult because of the lack of in situ measurements. The extensive high-quality surface radiative flux and meteorological measurements collected from MOSAiC provide a useful check on flux retrievals from CERES instruments. We compare MOSAiC and CERES surface radiative fluxes during October through March of 2019-2020 using the large set of meteorological measurements also collected by MOSAiC, specifically cloud properties. Previous work identified a significant source of error in the CERES estimate of surface downwelling longwave flux as the estimate of low level cloud amount when compared with MOSAiC W-band radar measurements. Continuing this work, we examine the effects of errors in cloud water path on surface radiative fluxes. When using all cloud conditions, errors in cloud water are also significantly correlated with surface radiative flux errors, though the size off the effect is only about half that of cloud amount. But when considering low cloud conditions only, the effects of cloud water and cloud amount are comparable.

J. Brant Dodson↗

Survey of microphysical properties of marine boundary-layer clouds in the Western North Atlantic

Oceanic low level clouds strongly affect the atmospheric radiation budget. Uncertainties in their microphysical properties and cover currently limit the accuracy of climate predictions. Further, studies quantifying the relative importance of aerosol and dynamics on cloud properties in specific meteorological regimes are poorly constrained by observations in the Western North Atlantic boundary layer. Low level clouds were measured during the Aerosol Cloud meTereology Interactions oVer the western ATlantic Experiment (ACTIVATE) campaign in winter and summer 2020. The two NASA LaRC research aircraft HU-25 Falcon and UC-12 B-200 King Air conducted 35 simultaneous flights to investigate aerosol-cloud interactions of maritime clouds and their impact on radiation. Number concentration, liquid water content, ice water content, and particle size distribution in the size range of 3 µm to 1460 µm in diameter were measured with the fast forward scattering cloud probe (FCDP) and 2-dimensional optical array imaging probe (2D-S) onboard the Falcon. Here, we present an overview of late winter (February-March) and late summer (August-September) oceanic cloud properties in the region 65°W to 80°W and 30°N to 40°N. We compare cloud properties in these two seasons and investigate their dependence on meteorological parameters and aerosol abundance. In a case study, we present cloud observations in a cold air outbreak event on 1 March 2020 with a specific focus on mixed-phase clouds.

microphysical properties↗

Meteorological Analysis of Icing Conditions Encountered in Low-Altitude Stratiform Clouds

Liquid-water content, droplet size, and temperature data measured during 22 flights in predominatly stratiform clouds through the 1948-49 and the 1949-50 winters are presented. Several icing encounters were of greater severity than those previously measured over the same geographical area, but were within the limits of similar measurements obtained over different terrain within the United States. An analysis of meteorological conditions existing during the 74 flights conducted for four winters indicated an inverse relation of liquid-water concentration to maximum horizontal extent of icing clouds. Data on the vertical extent of supercooled clouds are also presented. Icing conditions were most likely to occur in the southwest and northwest quadrants of a cyclone area, and least likely to occur in the southeast and northeast quadrants where convergent air flow and lifting over the associated warm frontal surface usually cause precipitation. Additional data indicated that, icing conditions were usually encountered in nonprecipitating clouds existing at subfreezing temperatures and were unlikely over areas where most weather observing stations reported the existence of precipitation. Measurements of liquid-water content obtained during 12 flights near the time and location of radiosonde observations were compared with theoretical values. The average liquid-water content of a cloud layer, as measured by the multicylinder technique, seldom exceeded two-thirds of that which could be released by adiabatic lifting. Local areas near the cloud tops equaled or occasionally exceeded the calculated maximum quantity of liquid water.

Kline, D. B.↗

Comparison of GLAS retrieved cloud fields with model generated rainfall fields

Monthly mean fractional cloud cover for January and February 1979, retrieved from SOP 1 of FGGE, are compared with the total precipitation field derived diagonally from the GLAS analysis/forecast system for the same time period. The breakdown of cloudiness into day (3 AM) and night (3 PM) is consistent with maps of outgoing long wave and short wave radiation inferred from AVHRR data. Of the many regions of coincidence, there is a particularly striking phenomenon: west of the coast of Peru, at about 20 deg S, there is a distinct small scale maximum in precipitation which coincides precisely with a maximum in the cloudiness field. This maximum in cloudiness and precipitation does not appear in the NOAA/NESS fields of albedo and outgoing long wave radiation which are normally sensitive to cloud fields. These low level clouds with warm tops are a mainly nocturnal phenomenon.

Susskind, J.↗

Numerical simulation of polar lows and comma clouds using simple dry models

Linear and nonlinear numerical channel models are used to simulate polar low/comma cloud evolution. The basic state of the model is idealized and can be specified analytically. It has strong horizontal as well as vertical wind shear and implicitly includes the effect of sensible heat fluxes from the lower boundary. This is done by having a layer of reduced stability present in the lower troposphere. The results of the linear model study are presented and used to provide input for the nonlinear model integration. It is shown that, given sufficient horizontal resolution, many features of polar low/comma clouds can be simulated by the nonlinear primitive equations model and the idealized basic state, in particular a rapidly growing disturbance with a wavelength on the order of 1000 km.

Mudrick, Stephen E.↗