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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A Novel Segmentation Algorithm for the ARM User Facility All-Sky Imagers Using Machine Learning Applications

Cloud cover plays a pivotal role in modulating the Earth's energy budget through the reflection of incoming solar radiation and the trapping of outgoing longwave radiation. Ground-based all-sky imagers offer an objective assessment of cloud cover that can be used to estimate solar irradiance, classify cloud types, track cloud movement, and serve as a benchmark 10 for the evaluation of satellite and reanalysis data products. The Atmospheric Radiation Measurement (ARM) user facility has utilized all-sky imagers for more than 25 years to monitor cloud cover and augment its comprehensive suite of atmospheric measurements. Following the retirement of its Total Sky Imager (TSI), ARM recently deployed the TSI’s successor, the All Sky Imager (ASI-16 camera systems). To provide a smooth transition and continuity to the vast amount of knowledge gathered by the TSI over the years, while addressing typical deployment issues, we developed a novel pixel segmentation algorithm, 15 the ASI Sky Cover (ASISKYCOVER). ASISKYCOVER builds on the different strengths and properties of the TSI processing algorithm while integrating machine learning techniques, ensuring data validity and accuracy across diverse atmospheric conditions. It enhances cloud cover characterization with new features such as artifact detection and uncertainty quantification. ASISKYCOVER also includes cloud cover estimates for near-zenith (narrow field-of-view) and reduces susceptibility to false detections. This study introduces ASISKYCOVER, details its algorithm framework, and demonstrates its capabilities using a 20 year-long dataset from the ARM Southern Great Plains site. Comparisons with co-located TSI data and other ARM measurements, such as zenith-pointing radars and lidars, are presented, underscoring the ASISKYCOVER’s potential to improve cloud cover analyses and data evaluation efforts, as well as to be integrated into higher-level data products that synergize instrument suites to generate new and insightful information

Silber, Israel↗
NASA NTRSDate not supplied

Automated Tracking of Shallow Cu Growth Rates on Geostationary Imagery and Linkages to Cloud Organization

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Common tropical cloud features, such as convective rolls and cold pool fronts, form and persist for different periods within environments that support such development. Determining differences in lifecycle amongst these features in varying environments requires viewing their evolution from initiation to decay. Geostationary satellites provide a means to follow the clouds with enhanced spatiotemporal sampling from space. We apply a cloud-tracking tool to study lifecycle properties of shallow cumulus sampled during the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) field campaign of 2019. The mission conducted airborne and shipborne operations over 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 on AHI 0.5-km visible reflectance and tracked during the daylit hours of several research flights that exhibited ideal atmospheric conditions for tracking. The resulting cloud tracks were collected according to regions containing airborne sampling of individual clouds at various stages of their lifecycles, yielding ensembles of tracks in separate environments. We present an analysis on lifecycle properties extracted from the cloud-track ensembles and their potential connections to cloud organizations observed throughout CAMP2Ex. Each ensemble is evaluated by calculating cloud-layer growth rates and comparing to spatial parameters, including track-achieved area and cloud-top height. The apparent clustering of growth rates for specific ensembles is then compared against overall cloud organizations, such as isolated congestus and cold pool fronts, that are observed with the airborne data. Finally, we consider how such differences in cloud growth appear in the airborne radar observations of intercepted cloud tracks.

Cloud Tracking↗
NASA NTRS1980

Short-interval SMS wind vector determinations for a severe local storms area

Short-interval SMS-2 visible digital image data are used to derive wind vectors from cloud tracking on time-lapsed sequences of geosynchronous satellite images. The cloud tracking areas are located in the Central Plains, where on May 6, 1975 hail-producing thunderstorms occurred ahead of a well defined dry line. Cloud tracking is performed on the Goddard Space Flight Center Atmospheric and Oceanographic Information Processing System. Lower tropospheric cumulus tracers are selected with the assistance of a cloud-top height algorithm. Divergence is derived from the cloud motions using a modified Cressman (1959) objective analysis technique which is designed to organize irregularly spaced wind vectors into uniformly gridded wind fields. The results demonstrate the feasibility of using satellite-derived wind vectors and their associated divergence fields in describing the conditions preceding severe local storm development. For this case, an area of convergence appeared ahead of the dry line and coincided with the developing area of severe weather. The magnitude of the maximum convergence varied between -10 to the -5th and -10 to the -14th per sec. The number of satellite-derived wind vectors which were required to describe conditions of the low-level atmosphere was adequate before numerous cumulonimbus cells formed. This technique is limited in areas of advanced convection.

Peslen, C. A.↗
NASA NTRS1994

High resolution cloud feature tracking on Venus by Galileo

The Venus cloud deck was monitored in February 1990 for 16 hours at 400 nanometers wavelength by the Galileo imaging system, with a spatial resolution of about 15 km and with image time separations as small as 10 minutes. Velocities are deduced by following the motion of small cloud features. In spite of the high temporal frequence is capable of being detected, no dynamical phenomena are apparent in the velocity data except the already well-known solar tides, possibly altered by the slow 4-day wave and the Hadley circulation. There is no evidence, to a level of approximately 4 m/s, of eddy or wavelike activity. The dominant size of sub-global scale albedo features is 200-500 km, and their contrast is approximately 5%. At low altitudes there are patches of blotchy, cell-like structures but at most locations the markings are streaky. The patterns are similar to those discovered by Mariner 10 and Pioneer Venus (M. J. S. Belton et al., 1976, W. B. Rossow et al., 1980). Scaling arguments are presented to argue that the mesoscale blotchy cell-like cloud patterns are caused by local dynamics driven in a shallow layer by differential absorption of sunlight. It is also argued that mesoscale albedo features are either streaky or cell-like simply depending on whether the horizontal shear of the large scale flow exceeds a certain critical value.

Toigo, Anthony↗
NASA NTRS2013

A Cross-Track Cloud-Scanning Dual-Frequency Doppler (C2D2) Radar for the Proposed ACE Mission and Beyond

The National Resource Council’s Earth Science Decadal Survey” (NRCDS) has identified the Aerosol/Climate/Ecosystems (ACE) Mission as a priority mission for NASA Earth science. The NRC recommended the inclusion of "a cross-track scanning cloud radar with channels at 94 GHz and possibly 34 GHz for measurement of cloud droplet size, glaciation height, and cloud height". Several radar concepts have been proposed that meet some of the requirements of the proposed ACE mission but none have provided scanning capability at both 34 and 94 GHz due to the challenge of constructing scanning antennas at 94 GHz. In this paper, we will describe a radar design that leverages new developments in microwave monolithic integrated circuits (MMICs) and micro-machining to enable an electronically-scanned radar with both Ka-band (35 GHz) and W-band (94-GHz) channels. This system uses a dual-frequency linear active electronically-steered array (AESA) combined with a parabolic cylindrical reflector. This configuration provides a large aperture (3m x 5m) with electronic-steering but is much simpler than a two-dimension AESA of similar size. Still, the W-band frequency requires element spacing of approximately 2.5 mm, presenting significant challenges for signal routing and incorporation of MMICs. By combining (Gallium Nitride) GaN MMIC technology with micro-machined radiators and interconnects and silicon-germanium (SiGe) beamforming MMICs, we are able to meet all the performance and packaging requirements of the linear array feed and enable simultaneous scanning of Ka-band and W-band radars over swath of up to 100 km.

Aerosol/Climate/Ecosystems (ACE) Mission↗
NASA NTRS1979

Impact of Short Interval SMS Digital Data on Wind Vector Determination for a Severe Local Storms Area

The impact of 5 minute interval SMS-2 visible digital image data in analyzing severe local storms is examined using wind vectors derived from cloud tracking on time lapsed sequence of geosynchronous satellite images. The cloud tracking areas are located in the Central Plains, where on 6 May 1975, hail-producing thunderstorms occurred ahead of a well defined dry line. The results demonstrate that satellite-derived wind vectors and their associated divergence fields complement conventional meteorological analyses in describing the conditions preceding severe local storm development.

Peslen, C. A.↗
NASA NTRSDate not supplied

Satellite Tracking of Shallow Cumulus during CAMP2Ex: The Aerosol and Organization Connection

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Shallow clouds come in many forms, from scattered, short-lived cumulus to organized features that include cold pool boundaries and lines reaching O(100 km) scale lasting several hours. In this study, we explore how cloud morphology and environmental aerosol affect shallow cumulus lifecycle properties. Measuring such influences requires a broad, detailed view of these cloud fields as they grow and decay. Geostationary satellites provide a means to follow the clouds with enhanced spatiotemporal sampling from space. We apply a cloud-tracking tool to study lifecycle properties of shallow cumulus sampled during the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) field campaign of 2019. The mission conducted airborne and shipborne operations over 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. We segment shallow cumulus on AHI 0.5-km visible reflectance during the daylit hours of several research flights that exhibited ideal atmospheric conditions for tracking. We collect the resulting cloud tracks by regions containing airborne sampling of the cloud environments and by two specific segmentation techniques: one optimized for small, disorganized cumulus and the other for larger, organized clouds using suitable thresholds for reflectance and blurring. We present an analysis of cloud lifecycle properties using our dual segmentation approach for various sampled environments of CAMP2Ex. A total of 7 research flights (RFs) exhibited ideal conditions for generating cloud-track ensembles under similar thermodynamic and kinematic profiles but with varying aerosol load. We consider lifetime, track-achieved metrics, and ensemble-fitted growth rates to evaluate the aerosol effect. Cloud elongation, a factor in cloud morphology, is also considered for any potential influence in observed shifts in growth rates. The results suggest that aerosol affects cloud lifecycles more significantly for clouds with larger areas and independent of the elongation factor.

Cloud Tracking↗
DOE OSTI2025

Mechanisms Behind the Long‐Distance Diurnal Offshore Precipitation Propagation in Northwestern South America

Abstract Northwestern South America (NWSA) is the rainiest region on Earth, with diurnal precipitation exhibiting extensive westward offshore propagation of up to about 1,200 km in boreal spring (March‐May). The diurnal offshore precipitation propagation begins slowly (3–10 m s −1 ) near the coast of NWSA (<200 km) but accelerates significantly (∼20 m s −1 ) and shows an afternoon enhancement far from the coast (>400 km). However, the driving mechanisms behind this long‐distance precipitation propagation remain unclear. Using a new cloud tracking and classification data set, we found that mesoscale convective systems (MCSs) are the dominant precipitation contributors in the offshore region of NWSA. Cloud tracking shows that the long‐distance propagation and the afternoon enhancement of diurnal precipitation primarily originate from MCSs initiated in the early morning, either over open oceans or from the coast of Central America. Composite tendency analysis shows that MCSs initiated near the coast of Central America have significant upward cooling and moistening signals starting from the surface before initiation. Further analysis of surface diurnal perturbation fields indicates that the land breeze is the primary driving mechanism for MCS initiation. Conversely, for MCSs initiated over open oceans, a significant downward cooling signal from 400 hPa is observed ∼7 hr before initiation, corresponding to the passage of diurnal gravity waves emitted from the Andes. Additionally, our findings highlight the critical role of lower and mid‐level moisture conditions in MCS initiation, alongside the influence of gravity waves.

Hu, Jingyi [Department of Meteorology and Atmosphe↗
NASA NTRS1977

Deriving winds for hurricanes using short interval satellite imagery

Results are presented for a study program designed to develop a better means of obtaining wind data needed by hurricane forecasters and to determine the optimum space and time resolution of satellite data used to obtain such winds. The discussion covers cloud tracking with an image display and manipulation system and analysis of IR imagery of Hurricane Eloise. It is shown that greater resolution in time and space of satellite imagery made it possible to derive up to six times as many low-level winds in a hurricane case, to eliminate 'bad winds' caused by mistaking cloud growth for cloud motion, and to remove ambiguities that would have caused difficulty in tracking clouds using only the imagery taken at 30-min intervals. It is suggested to use short-interval imagery (less than 10 min) for wind determination for future research in areas of tropical cyclones.

Gentry, R. C.↗
NASA NTRS1993

Jupiter's winds and Arnol'd's second stability theorem: Slowly moving waves and neutral stability

Since the Voyager encounters in 1979, it has been known that Jupiter's cloud-top zonal winds violate the barotropic stability criterion. A vortex-tube stretching analysis of the Voyager wind data indicates that the more general Charney-Stern stability criterion is also violated. On the other hand, the zonal winds determined by tracking cloud features in Hubble Space Telescope images taken in 1991 precisely match the zonal winds determined by tracking cloud features in Voyager images, and it is hard to understand how a complicated zonal wind profile like Jupiter's could be unstable and yet not change at all in 12 years. In fact, there are at least two unknown ways to violate the Charney-Stern stability criterion and still have a stable flow. The better known of these is called Fjortoft's theorem, or Arnol'd's 1st theorem for the case of large-amplitude perturbations. Although the Fjortoft-Arnol'd theorem has been extended from the quasi-geostrophic equations to the primitive equations, the basic requirement that the potential vorticity be an increasing function of streamfunction is opposite to the case found in Jupiter, where the Voyager data indicate that the potential vorticity is a decreasing function of streamfunction. But this second case is precisely that which is covered by Arnol'd's 2nd stability theorem. In fact, the Voyager data suggest that Jupiter's zonal winds are neutrally stable with respect to Arnol'd's 2nd stability theorem. Here, we analyze the linear stability problem of a one-parameter family of sinusoidal zonal wind profiles that are close to neutral stability with respect to Arnol'd's 2nd stability theorem. We find numerically that the most unstable mode is always stationary, which may help to explain the slowly moving mode 10 waves observed on Jupiter. We find that violation of Arnol'd's 2nd stability theorem is both necessary and sufficient for instability of sinusoidal profiles. However, there appears to be no simple extension of Arnol'd's 2nd stability theorem to the primitive equations. Nevertheless, the primitive growth rates are small, and the primitive system is still governed by the quasi-geostrophic neutral-stability configuration.

Stamp, Andrew P.↗
NASA NTRS1979

The benefits of using short-interval satellite images to derive winds for tropical cyclones

During the 1975, 1976 and 1977 North Atlantic hurricane seasons, NOAA/NESS and NASA/GSFC conducted a cooperative program to determine the best resolution and frequency now available from satellite images for deriving winds to study and forecast tropical cyclones. High spatial and temporal resolution satellite imagery made it feasible to provide a large number of lower and upper tropospheric winds which can be obtained by tracking clouds within 650 km of tropical cyclone centers. Up to 10 (5) times as many low-level winds were derived from images spaced at 3 or 7.5 min intervals as from those at 30 min (15 min) intervals. Rapid-scan full-resolution IR and visible images minimized the 'erroneous' winds derived by tracking cloud elements that propagate by growing on one side and dissipating on the other and by tracking repetitive patterns that provided ambiguous indications of direction of movement.

Rodgers, E.↗
NASA NTRS1986

Cloud-top meridional momentum transports on Saturn and Jupiter

Cloud-tracked wind measurements reported by Sromovsky et al. were analyzed to determine meridional momentum transports in Saturn's northern middle latitudes. Results are expressed in terms of eastward and northward velocity components (u and v), and eddy components u and v. At most latitudes between 13 and 44 deg N (planetocentric), the transport by the mean flow ( ) is measurably southward, tending to support Saturn's large equatorial jet, and completely dominating the eddy transport. Meridional velocities are near zero at the peak of the relatively weak westward jet; along the flanks of that jet, measurements indicate divergent flow out of the jet. In this region the dominant eddy transport ( ) is northward on the north side of the jet, but not resolvable on the south side. Eddy transports at most other latitudes are not significantly different from measurement error. The conversion of eddy kinetic energy to mean kinetic energy, indicated by the correlation between and d /dy (where y is meridional distance) is clearly smaller than various values reported for Jupiter, and not significantly different from zero. Both Jovian and Saturnian results may be biased by the tendency for cloud tracking to favor high contrast features, and thus may not be entirely representative of the cloud level motions as a whole.

Stromovsky, L. A.↗
NASA NTRS1977

A satellite interpretation of the dynamics of a severe local storms area using 5 minute interval SMS data

Wind fields derived from cloud-tracking on the visible digital data of the Synchronous Meteorological Satellite-2 are used to study the onset of local severe storms. The study is based on an assessment of several dynamic parameters of lower tropospheric wind fields, including the divergence, relative vorticity, and deformation. The automated cloud-tracking proves capable of detecting a preferred area of flow convergence located ahead of a dry line; the detection of this convergence aids in monitoring the onset of a hail-producing thunderstorm.

Peslen, C. A.↗
NASA NTRS1983

The special effort processing of FGGE data

The basic FGGE level IIb data set was enhanced. It focused on removing deficiencies in the objective methods of quality assurance, removing efficiencies in certain types of operationally produced satellite soundings, and removing deficiencies in certain types of operationally produced cloud tracked winds. The Special Effort was a joint NASA-NOAA-University of Wisconsin effort. The University of Wisconsin installed an interactive McIDAS capability on the Amdahl computer at the Goddard Laboratory of Atmospheric Sciences (GLAS) with one interactive video terminal at Goddard and the other at the World Weather Building. With this interactive capability a joint processing effort was undertaken to reprocess certain FGGE data sets. NOAA produced a specially edited data set for the special observing periods (SOPs) of FGGE. NASA produced an enhanced satellite sounding data set for the SOPs while the University of Wisconsin produced an enhanced cloud tracked wind set from the Japanese geostationary satellite images.

Source record↗
NASA NTRS2024

Three-Dimensional Atmospheric Dynamics of Jupiter from Ground-Based Doppler Imaging Spectroscopy in the Visible

We present three-dimensional (3D) maps of Jupiter’s atmospheric circulation at cloud-top level from Doppler-imaging data obtained in the visible domain with JIVE, the second node of the JOVIAL network, which is mounted on the Dunn Solar Telescope at Sunspot, New Mexico. We report on 12 nights of observations between May 4 and May 30, 2018, representing a total of about 80 hours. Firstly, the average zonal wind profile derived from our data is compatible with that derived from cloud-tracking measurements performed on Hubble Space Telescope images obtained in April 2018 from the Outer Planet Atmospheres Legacy (OPAL) program. Secondly, we present the first ever two-dimensional maps of Jupiter’s atmospheric circulation from Doppler measurements. The zonal velocity map highlights well-known atmospheric features, such as the equatorial hot spots and the Great Red Spot (GRS). In addition to zonal winds, we derive meridional and vertical velocity fields from the Doppler data. The motions attributed to vertical flows are mainly located at the boundary between the equatorial belts and tropical zones, which could indicate active motion in these regions. Qualitatively, these results compare well to recent Juno data that have unveiled the three-dimensional structure of Jupiter’s wind field. To the contrary, the motions attributed to meridional circulation are very different from what is obtained by cloud tracking, except at the GRS. Because of limitations with data resolution and processing techniques, we acknowledge that our measurement of vertical or meridional flows of Jupiter are still to be confirmed.

Francois-Xavier Schmider↗
DOE OSTI2021

Mesoscale Convective Systems Dominate the Energetics of the South Asian Summer Monsoon Onset

The onset of the South Asian summer monsoon (SASM) is featured as an abrupt increase of precipitation and atmospheric column-integrated moist static energy (MSE). Using convection permitting simulations, a novel cloud tracking technique, and an MSE budget, the relative roles of mesoscale convective systems (MCSs) and non-MCS isolated deep convection in the SASM onset are studied. The analysis shows MCSs play a crucial role in the sudden increases of rainfall, diabatic MSE sources, and the subsequent enhanced export of column-integrated MSE during the onset. A “diabatic sources-energy export” plane analysis delineates the different roles of MCSs and non-MCS deep convection in the SASM onset. Although deep convection always leads to a net energy export, mesoscale organization of deep convection dominates the convection associated positive feedbacks that accelerate the energy cycle of the SASM onset. Sensitivity experiment shows that the results are insensitive to the model resolutions.

Chen, Xingchao↗
NASA NTRS2016

CubeSat Constellation Cloud Winds(C3Winds) A New Wind Observing System to Study Mesoscale Cloud Dynamics and Processes

The CubeSat Constellation Cloud Winds (C3Winds) is a NASA Earth Venture Instrument (EV-I) concept with the primary objective to better understand mesoscale dynamics and their structures in severe weather systems. With potential catastrophic damage and loss of life, strong extratropical and tropical cyclones (ETCs and TCs) have profound three-dimensional impacts on the atmospheric dynamic and thermodynamic structures, producing complex cloud precipitation patterns, strong low-level winds, extensive tropopause folds, and intense stratosphere-troposphere exchange. Employing a compact, stereo IR-visible imaging technique from two formation-flying CubeSats, C3Winds seeks to measure and map high-resolution (2 km) cloud motion vectors (CMVs) and cloud geometric height (CGH) accurately by tracking cloud features within 5-15 min. Complementary to lidar wind observations from space, the high-resolution wind fields from C3Winds will allow detailed investigations on strong low-level wind formation in an occluded ETC development, structural variations of TC inner-core rotation, and impacts of tropopause folding events on tropospheric ozone and air quality. Together with scatterometer ocean surface winds, C3Winds will provide a more comprehensive depiction of atmosphere-boundary-layer dynamics and interactive processes. Built upon mature imaging technologies and long history of stereoscopic remote sensing, C3Winds provides an innovative, cost-effective solution to global wind observations with potential of increased diurnal sampling via CubeSat constellation.

mesoscale dynamics↗
DOE OSTI2023

A semi-Lagrangian method for detecting and tracking deep convective clouds in geostationary satellite observations

Automated methods for the detection and tracking of deep convective clouds in geostationary satellite imagery have a vital role in both the forecasting of severe storms and research into their behaviour. Studying the interactions and feedbacks between multiple deep convective clouds (DCC), however, poses a challenge for existing algorithms due to the necessary compromise between false detection and missed detection errors. We utilise an optical flow method to determine the motion of deep convective clouds in GOES-16 ABI imagery in order to construct a semi-Lagrangian framework for the motion of the cloud field, independently of the detection and tracking of cloud objects. The semi-Lagrangian framework allows severe storms to be simultaneously detected and tracked in both spatial and temporal dimensions. For the purpose of this framework we have developed a novel Lagrangian convolution method and a number of novel implementations of morphological image operations that account for the motion of observed objects. These novel methods allow the accurate extension of computer vision techniques to the temporal domain for moving objects such as DCCs. By combining this framework with existing methods for detecting DCCs (including detection of growing cores through cloud top cooling and detection of anvil clouds using brightness temperature), we show that the novel framework enables reductions in errors due to both false and missed detections compared to any of the individual methods, reducing the need to compromise when compared with existing frameworks. The novel framework enables the continuous tracking of anvil clouds associated with detected deep convection after convective activity has stopped, enabling the study of the entire life cycle of DCCs and their associated anvils. Furthermore, we expect this framework to be applicable to a wide range of cases including the detection and tracking of low-level clouds and other atmospheric phenomena. In addition, this framework may be used to combine observations from multiple sources, including satellite observations, weather radar and reanalysis model data.

54 ENVIRONMENTAL SCIENCES↗