A Local Index of Cloud Immersion in Tropical Forests Using Time-Lapse Photography

NASA Astrophysics Data System (ADS)

Bassiouni, M.; Scholl, M. A.

2015-12-01

Data on the frequency, duration and elevation of cloud immersion is essential to improve estimates of cloud water deposition in water budgets in cloud forests. Here, we present a methodology to detect local cloud immersion in remote tropical forests using time-lapse photography. A simple approach is developed to detect cloudy conditions in photographs within the canopy where image depth during clear conditions may be less than 10 meters and moving leaves and branches and changes in lighting are unpredictable. A primary innovation of this study is that cloudiness is determined from images without using a reference clear image and without minimal threshold value determination or human judgment for calibration. Five sites ranging from 600 to 1000 meters elevation along a ridge in the Luquillo Critical Zone Observatory, Puerto Rico were each equipped with a trail camera programmed to take an image every 30 minutes since March 2014. Images were classified using four selected cloud-sensitive image characteristics (SCICs) computed for small image regions: contrast, the coefficient of variation and the entropy of the luminance of each image pixel, and image colorfulness. K-means clustering provided reasonable results to discriminate cloudy from clear conditions. Preliminary results indicate that 79-94% (daytime) and 85-93% (nighttime) of validation images were classified accurately at one open and two closed canopy sites. The euclidian distances between SCICs vectors of images during cloudy conditions and the SCICs vector of the centroid of the cluster of clear images show potential to quantify cloud density in addition to immersion. The classification method will be applied to determine spatial and temporal patterns of cloud immersion in the study area. The presented approach offers promising applications to increase observations of low-lying clouds at remote mountain sites where standard instruments to measure visibility and cloud base may not be practical.

Pattern recognition of satellite cloud imagery for improved weather prediction

NASA Technical Reports Server (NTRS)

Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.

1986-01-01

The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.

Clouds Sailing Above Martian Horizon, Enhanced

NASA Image and Video Library

2017-08-09

Clouds drift across the sky above a Martian horizon in this accelerated sequence of enhanced images from NASA's Curiosity Mars rover. The rover's Navigation Camera (Navcam) took these eight images over a span of four minutes early in the morning of the mission's 1,758th Martian day, or sol (July 17, 2017), aiming toward the south horizon. They have been processed by first making a "flat field' adjustment for known differences in sensitivity among pixels and correcting for camera artifacts due to light reflecting within the camera, and then generating an "average" of all the frames and subtracting that average from each frame. This subtraction emphasizes changes whether due to movement -- such as the clouds' motion -- or due to lighting -- such as changing shadows on the ground as the morning sunlight angle changed. On the same Martian morning, Curiosity also observed clouds nearly straight overhead. The clouds resemble Earth's cirrus clouds, which are ice crystals at high altitudes. These Martian clouds are likely composed of crystals of water ice that condense onto dust grains in the cold Martian atmosphere. Cirrus wisps appear as ice crystals fall and evaporate in patterns known as "fall streaks" or "mare's tails." Such patterns have been seen before at high latitudes on Mars, for instance by the Phoenix Mars Lander in 2008, and seasonally nearer the equator, for instance by the Opportunity rover. However, Curiosity has not previously observed such clouds so clearly visible from the rover's study area about five degrees south of the equator. The Hubble Space Telescope and spacecraft orbiting Mars have observed a band of clouds to appear near the Martian equator around the time of the Martian year when the planet is farthest from the Sun. With a more elliptical orbit than Earth's, Mars experiences more annual variation than Earth in its distance from the Sun. The most distant point in an orbit around the Sun is called the aphelion. The near-equatorial Martian cloud pattern observed at that time of year is called the "aphelion cloud belt." These new images from Curiosity were taken about two months before aphelion, but the morning clouds observed may be an early stage of the aphelion cloud belt. An animation is available at https://photojournal.jpl.nasa.gov/catalog/PIA21840

Empirical orthogonal function analysis of cloud-containing coastal zone color scanner images of northeastern North American coastal waters

NASA Technical Reports Server (NTRS)

Eslinger, David L.; O'Brien, James J.; Iverson, Richard L.

1989-01-01

Empirical-orthogonal-function (EOF) analyses were carried out on 36 images of the Mid-Atlantic Bight and the Gulf of Maine, obtained by the CZCS aboard Nimbus 7 for the time period from February 28 through July 9, 1979, with the purpose of determining pigment concentrations in coastal waters. The EOF procedure was modified so as to include images with significant portions of data missing due to cloud obstruction, making it possible to estimate pigment values in areas beneath clouds. The results of image analyses explained observed variances in pigment concentrations and showed a south-to-north pattern corresponding to an April Mid-Atlantic Bight bloom and a June bloom over Nantucket Shoals and Platts Bank.

Voyager 2 Jupiter Eruption Movie

NASA Technical Reports Server (NTRS)

2000-01-01

This movie records an eruptive event in the southern hemisphere of Jupiter over a period of 8 Jupiter days. Prior to the event, an undistinguished oval cloud mass cruised through the turbulent atmosphere. The eruption occurs over avery short time at the very center of the cloud. The white eruptive material is swirled about by the internal wind patterns of the cloud. As a result of the eruption, the cloud then becomes a type of feature seen elsewhere on Jupiter known as 'spaghetti bowls'.

As Voyager 2 approached Jupiter in 1979, it took images of the planet at regular intervals. This sequence is made from 8 images taken once every Jupiter rotation period (about 10 hours). These images were acquired in the Violet filter around May 6, 1979. The spacecraft was about 50 million kilometers from Jupiter at that time.

This time-lapse movie was produced at JPL by the Image Processing Laboratory in 1979.

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures

NASA Technical Reports Server (NTRS)

Key, J.

1990-01-01

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.

Investigation of mesoscale cloud features viewed by LANDSAT

NASA Technical Reports Server (NTRS)

Sherr, P. E. (Principal Investigator); Feteris, P. J.; Lisa, A. S.; Bowley, C. J.; Fowler, M. G.; Barnes, J. C.

1976-01-01

The author has identified the following significant results. Some 50 LANDSAT images displaying mesoscale cloud features were analyzed. This analysis was based on the Rayleigh-Kuettner model describing the formation of that type of mesoscale cloud feature. This model lends itself to computation of the average wind speed in northerly flow from the dimensions of the cloud band configurations measured from a LANDSAT image. In nearly every case, necessary conditions of a curved wind profile and orientation of the cloud streets within 20 degrees of the direction of the mean wind in the convective layer were met. Verification of the results by direct observation was hampered, however, by the incompatibility of the resolution of conventional rawinsonde observations with the scale of the banded cloud patterns measured from LANDSAT data. Comparison seems to be somewhat better in northerly flows than in southerly flows, with the largest discrepancies in wind speed being within 8m/sec, or a factor of two.

Introducing two Random Forest based methods for cloud detection in remote sensing images

NASA Astrophysics Data System (ADS)

Ghasemian, Nafiseh; Akhoondzadeh, Mehdi

2018-07-01

Cloud detection is a necessary phase in satellite images processing to retrieve the atmospheric and lithospheric parameters. Currently, some cloud detection methods based on Random Forest (RF) model have been proposed but they do not consider both spectral and textural characteristics of the image. Furthermore, they have not been tested in the presence of snow/ice. In this paper, we introduce two RF based algorithms, Feature Level Fusion Random Forest (FLFRF) and Decision Level Fusion Random Forest (DLFRF) to incorporate visible, infrared (IR) and thermal spectral and textural features (FLFRF) including Gray Level Co-occurrence Matrix (GLCM) and Robust Extended Local Binary Pattern (RELBP_CI) or visible, IR and thermal classifiers (DLFRF) for highly accurate cloud detection on remote sensing images. FLFRF first fuses visible, IR and thermal features. Thereafter, it uses the RF model to classify pixels to cloud, snow/ice and background or thick cloud, thin cloud and background. DLFRF considers visible, IR and thermal features (both spectral and textural) separately and inserts each set of features to RF model. Then, it holds vote matrix of each run of the model. Finally, it fuses the classifiers using the majority vote method. To demonstrate the effectiveness of the proposed algorithms, 10 Terra MODIS and 15 Landsat 8 OLI/TIRS images with different spatial resolutions are used in this paper. Quantitative analyses are based on manually selected ground truth data. Results show that after adding RELBP_CI to input feature set cloud detection accuracy improves. Also, the average cloud kappa values of FLFRF and DLFRF on MODIS images (1 and 0.99) are higher than other machine learning methods, Linear Discriminate Analysis (LDA), Classification And Regression Tree (CART), K Nearest Neighbor (KNN) and Support Vector Machine (SVM) (0.96). The average snow/ice kappa values of FLFRF and DLFRF on MODIS images (1 and 0.85) are higher than other traditional methods. The quantitative values on Landsat 8 images show similar trend. Consequently, while SVM and K-nearest neighbor show overestimation in predicting cloud and snow/ice pixels, our Random Forest (RF) based models can achieve higher cloud, snow/ice kappa values on MODIS and thin cloud, thick cloud and snow/ice kappa values on Landsat 8 images. Our algorithms predict both thin and thick cloud on Landsat 8 images while the existing cloud detection algorithm, Fmask cannot discriminate them. Compared to the state-of-the-art methods, our algorithms have acquired higher average cloud and snow/ice kappa values for different spatial resolutions.

Cloud Streets over the Bering Sea

NASA Image and Video Library

2017-12-08

NASA image captured January 4, 2012 Most of us prefer our winter roads free of ice, but one kind of road depends on it: a cloud street. Such streets formed over the Bering Sea in early January 2012, thanks to snow and ice blanketing the nearby land, and sea ice clinging to the shore. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite captured this natural-color image of the cloud streets on January 4, 2012. Air blowing over frigid ice then warmer ocean water can lead to the development of parallel cylinders of spinning air. Above the upward cycle of these cylinders (rising air), small clouds form. Along the downward cycle (descending air), skies are clear. The resulting cloud formations resemble streets. This image shows that some of the cloud streets begin over the sea ice, but most of the clouds hover over the open ocean water. These streets are not perfectly straight, but curve to the east and west after passing over the sea ice. By lining up along the prevailing wind direction, the tiny clouds comprising the streets indicate the wind patterns around the time of their formation. NASA images courtesy LANCE/EOSDIS MODIS Rapid Response Team at NASA GSFC. Caption by Michon Scott. Instrument: Terra - MODIS Credit: NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Monte Carlo Radiative Transfer Modeling of Lightning Observed in Galileo Images of Jupiter

NASA Technical Reports Server (NTRS)

Dyudine, U. A.; Ingersoll, Andrew P.

2002-01-01

We study lightning on Jupiter and the clouds illuminated by the lightning using images taken by the Galileo orbiter. The Galileo images have a resolution of 25 km/pixel and axe able to resolve the shape of the single lightning spots in the images, which have full widths at half the maximum intensity in the range of 90-160 km. We compare the measured lightning flash images with simulated images produced by our ED Monte Carlo light-scattering model. The model calculates Monte Carlo scattering of photons in a ED opacity distribution. During each scattering event, light is partially absorbed. The new direction of the photon after scattering is chosen according to a Henyey-Greenstein phase function. An image from each direction is produced by accumulating photons emerging from the cloud in a small range (bins) of emission angles. Lightning bolts are modeled either as points or vertical lines. Our results suggest that some of the observed scattering patterns axe produced in a 3-D cloud rather than in a plane-parallel cloud layer. Lightning is estimated to occur at least as deep as the bottom of the expected water cloud. For the six cases studied, we find that the clouds above the lightning are optically thick (tau > 5). Jovian flashes are more regular and circular than the largest terrestrial flashes observed from space. On Jupiter there is nothing equivalent to the 30-40-km horizontal flashes which axe seen on Earth.

Cloud Arcs in the Western Pacific

NASA Technical Reports Server (NTRS)

2002-01-01

Small cumulus clouds in this natural-color view from the Multi-angle Imaging SpectroRadiometer have formed a distinctive series of quasi-circular arcs. Clues regarding the formation of these arcs can be found by noting that larger clouds exist in the interior of each arc.

The interior clouds are thicker and likely to be more convectively active than the other clouds, causing much of the air near the centers of the arcs to rise. This air spreads out horizontally in all directions as it rises and continues to spread out as it begins to sink back to the surface. This pushes any existing small cumulus clouds away from the central region of convection.

As the air sinks, it also warms, preventing other small clouds from forming, so that the regions just inside the arcs are kept clear. At the arcs, the horizontal flow of sinking air is now quite weak and on meeting the undisturbed air it can rise again slightly -- possibly assisting in the formation of new small cumulus clouds. Although examples of the continuity of air, in which every rising air motion must be compensated by a sinking motion elsewhere, are very common, the degree of organization exhibited here is relatively rare, as the wind field at different altitudes usually disrupts such patterns. The degree of self organization of this cloud image, whereby three or four such circular events form a quasi-periodic pattern, probably also requires a relatively uncommon combination of wind, temperature and humidity conditions for it to occur.

The image was acquired by MISR's nadir camera on March 11, 2002, and is centered west of the Marshall Islands. Enewetak Atoll is discernible through thin cloud as the turquoise band near the right-hand edge of the image.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and views almost the entire globe every 9 days. This image is a portion of the data acquired during Terra orbit 11863, and covers an area of about 380 kilometers x 345 kilometers. It utilizes data from blocks 80 to 82 within World Reference System-2 path 90.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

a Low-Cost and Portable System for 3d Reconstruction of Texture-Less Objects

NASA Astrophysics Data System (ADS)

Hosseininaveh, A.; Yazdan, R.; Karami, A.; Moradi, M.; Ghorbani, F.

2015-12-01

The optical methods for 3D modelling of objects can be classified into two categories including image-based and range-based methods. Structure from Motion is one of the image-based methods implemented in commercial software. In this paper, a low-cost and portable system for 3D modelling of texture-less objects is proposed. This system includes a rotating table designed and developed by using a stepper motor and a very light rotation plate. The system also has eight laser light sources with very dense and strong beams which provide a relatively appropriate pattern on texture-less objects. In this system, regarding to the step of stepper motor, images are semi automatically taken by a camera. The images can be used in structure from motion procedures implemented in Agisoft software.To evaluate the performance of the system, two dark objects were used. The point clouds of these objects were obtained by spraying a light powders on the objects and exploiting a GOM laser scanner. Then these objects were placed on the proposed turntable. Several convergent images were taken from each object while the laser light sources were projecting the pattern on the objects. Afterward, the images were imported in VisualSFM as a fully automatic software package for generating an accurate and complete point cloud. Finally, the obtained point clouds were compared to the point clouds generated by the GOM laser scanner. The results showed the ability of the proposed system to produce a complete 3D model from texture-less objects.

Waves on White: Ice or Clouds?

NASA Technical Reports Server (NTRS)

2005-01-01

As it passed over Antarctica on December 16, 2004, the Multi-angle Imaging SpectroRadiometer (MISR) on NASA's Terra satellite captured this image showing a wavy pattern in a field of white. At most other latitudes, such wavy patterns would likely indicate stratus or stratocumulus clouds. MISR, however, saw something different. By using information from several of its multiple cameras (each of which views the Earth's surface from a different angle), MISR was able to tell that what looked like a wavy cloud pattern was actually a wavy pattern on the ice surface. One of MISR's cloud classification products, the Angular Signature Cloud Mask (ASCM), correctly identified the rippled area as being at the surface.

In this image pair, the view from MISR's most oblique backward-viewing camera is on the left, and the color-coded image on the right shows the results of the ASCM. The colors represent the level of certainty in the classification. Areas that were classed as cloudy with high confidence are white, and areas where the confidence was lower are yellow; dark blue shows confidently clear areas, while light blue indicates clear with lower confidence. The ASCM works particularly well at detecting clouds over snow and ice, but also works well over ocean and land. The rippled area on the surface which could have been mistaken for clouds are actually sastrugi -- long wavelike ridges of snow formed by the wind and found on the polar plains. Usually sastrugi are only several centimeters high and several meters apart, but large portions of East Antarctica are covered by mega-sastrugi ice fields, with dune-like features as high as four meters separated by two to five kilometers. The mega-sastrugi fields are a result of unusual snow accumulation and redistribution processes influenced by the prevailing winds and climate conditions. MISR imagery indicates that these mega sastrugi were stationary features between 2002 and 2004.

Being able to distinguish clouds from snow or ice-covered surfaces is important in order to adequately characterize the radiation balance of the polar regions. However, detecting clouds using spaceborne detectors over snow and ice surfaces is notoriously difficult, because the surface may often be as bright and as cold as the overlying clouds, and because polar atmospheric temperature inversions sometimes mean that clouds are warmer than the underlying snow or ice surface. The Angular Signature Cloud Mask (ASCM) was developed based on the Band-Differenced Angular Signature (BDAS) approach, introduced by Di Girolamo and Davies (1994) and updated for MISR application by Di Girolamo and Wilson (2003). BDAS uses both spectral and angular changes in reflectivity to distinguish clouds from the background, and the ASCM calculates the difference between the 446 and 866 nanometer reflectances at MISR's two most oblique cameras that view forward-scattered light. New land thresholds for the ASCM are planned for delivery later this year.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82o north and 82o south latitude. This image area covers about 277 kilometers by 421 kilometers in the interior of the East Antarctic ice sheet. These data products were generated from a portion of the imagery acquired during Terra orbit 26584 and utilize data from within blocks 159 to 161 within World Reference System-2 path 63.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

An Automatic Cloud Mask Algorithm Based on Time Series of MODIS Measurements

NASA Technical Reports Server (NTRS)

Lyapustin, Alexei; Wang, Yujie; Frey, R.

2008-01-01

Quality of aerosol retrievals and atmospheric correction depends strongly on accuracy of the cloud mask (CM) algorithm. The heritage CM algorithms developed for AVHRR and MODIS use the latest sensor measurements of spectral reflectance and brightness temperature and perform processing at the pixel level. The algorithms are threshold-based and empirically tuned. They don't explicitly address the classical problem of cloud search, wherein the baseline clear-skies scene is defined for comparison. Here, we report on a new CM algorithm which explicitly builds and maintains a reference clear-skies image of the surface (refcm) using a time series of MODIS measurements. The new algorithm, developed as part of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm for MODIS, relies on fact that clear-skies images of the same surface area have a common textural pattern, defined by the surface topography, boundaries of rivers and lakes, distribution of soils and vegetation etc. This pattern changes slowly given the daily rate of global Earth observations, whereas clouds introduce high-frequency random disturbances. Under clear skies, consecutive gridded images of the same surface area have a high covariance, whereas in presence of clouds covariance is usually low. This idea is central to initialization of refcm which is used to derive cloud mask in combination with spectral and brightness temperature tests. The refcm is continuously updated with the latest clear-skies MODIS measurements, thus adapting to seasonal and rapid surface changes. The algorithm is enhanced by an internal dynamic land-water-snow classification coupled with a surface change mask. An initial comparison shows that the new algorithm offers the potential to perform better than the MODIS MOD35 cloud mask in situations where the land surface is changing rapidly, and over Earth regions covered by snow and ice.

A Jovian Hotspot in True and False Colors (Time set 3)

NASA Technical Reports Server (NTRS)

1997-01-01

True and false color views of an equatorial 'hotspot' on Jupiter. These images cover an area 34,000 kilometers by 11,000 kilometers. The top mosaic combines the violet (410 nanometers or nm) and near-infrared continuum (756 nm) filter images to create an image similar to how Jupiter would appear to human eyes. Differences in coloration are due to the composition and abundances of trace chemicals in Jupiter's atmosphere. The bottom mosaic uses Galileo's three near-infrared wavelengths (756 nm, 727 nm, and 889 nm displayed in red, green, and blue) to show variations in cloud height and thickness. Bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the deep cloud with an overlying thin haze. The light blue region to the left is covered by a very high haze layer. The multicolored region to the right has overlapping cloud layers of different heights. Galileo is the first spacecraft to distinguish cloud layers on Jupiter.

North is at the top. The mosaics cover latitudes 1 to 10 degrees and are centered at longitude 336 degrees West. The planetary limb runs along the right edge of the image. Cloud patterns appear foreshortened as they approach the limb. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers by the Solid State Imaging system aboard NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

The analysis of image feature robustness using cometcloud

PubMed Central

Qi, Xin; Kim, Hyunjoo; Xing, Fuyong; Parashar, Manish; Foran, David J.; Yang, Lin

2012-01-01

The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illumination, noise, compression, distortion, and rotation. We employed five texture analysis methods and tested them while introducing all of the challenges listed above. The texture features that were evaluated include co-occurrence matrix, center-symmetric auto-correlation, texture feature coding method, local binary pattern, and texton. Due to the independence of each transformation and texture descriptor, a network structured combination was proposed and deployed on the Rutgers private cloud. The experiments utilized 20 randomly selected tissue microarray cores. All the combinations of the image transformations and deformations are calculated, and the whole feature extraction procedure was completed in 70 minutes using a cloud equipped with 20 nodes. Center-symmetric auto-correlation outperforms all the other four texture descriptors but also requires the longest computational time. It is roughly 10 times slower than local binary pattern and texton. From a speed perspective, both the local binary pattern and texton features provided excellent performance for classification and content-based image retrieval. PMID:23248759

Jupiter's Northern Hemisphere in False Color (Time Set 3)

NASA Technical Reports Server (NTRS)

1997-01-01

Mosaic of Jupiter's northern hemisphere between 10 and 50 degrees latitude. Jupiter's atmospheric circulation is dominated by alternating eastward and westward jets from equatorial to polar latitudes. The direction and speed of these jets in part determine the color and texture of the clouds seen in this mosaic. Also visible are several other common Jovian cloud features, including large white ovals, bright spots, dark spots, interacting vortices, and turbulent chaotic systems. The north-south dimension of each of the two interacting vortices in the upper half of the mosaic is about 3500 kilometers.

This mosaic uses the Galileo imaging camera's three near-infrared wavelengths (756 nanometers, 727 nanometers, and 889 nanometers displayed in red, green, and blue) to show variations in cloud height and thickness. Light blue clouds are high and thin, reddish clouds are deep, and white clouds are high and thick. The clouds and haze over the ovals are high, extending into Jupiter's stratosphere. Dark purple most likely represents a high haze overlying a clear deep atmosphere. Galileo is the first spacecraft to distinguish cloud layers on Jupiter.

North is at the top. The images are projected on a sphere, with features being foreshortened towards the north. The planetary limb runs along the right edge of the mosaic. Cloud patterns appear foreshortened as they approach the limb. The smallest resolved features are tens of kilometers in size. These images were taken on April 3, 1997, at a range of 1.4 million kilometers by the Solid State Imaging system (CCD) on NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

A portable low-cost 3D point cloud acquiring method based on structure light

NASA Astrophysics Data System (ADS)

Gui, Li; Zheng, Shunyi; Huang, Xia; Zhao, Like; Ma, Hao; Ge, Chao; Tang, Qiuxia

2018-03-01

A fast and low-cost method of acquiring 3D point cloud data is proposed in this paper, which can solve the problems of lack of texture information and low efficiency of acquiring point cloud data with only one pair of cheap cameras and projector. Firstly, we put forward a scene adaptive design method of random encoding pattern, that is, a coding pattern is projected onto the target surface in order to form texture information, which is favorable for image matching. Subsequently, we design an efficient dense matching algorithm that fits the projected texture. After the optimization of global algorithm and multi-kernel parallel development with the fusion of hardware and software, a fast acquisition system of point-cloud data is accomplished. Through the evaluation of point cloud accuracy, the results show that point cloud acquired by the method proposed in this paper has higher precision. What`s more, the scanning speed meets the demand of dynamic occasion and has better practical application value.

Open-cell and closed-cell clouds off Peru [detail

NASA Image and Video Library

2017-12-08

2010/107 - 04/17 at 21 :05 UTC. Open-cell and closed-cell clouds off Peru, Pacific Ocean. To view the full fame of this image to go: www.flickr.com/photos/gsfc/4557497219/ Resembling a frosted window on a cold winter's day, this lacy pattern of marine clouds was captured off the coast of Peru in the Pacific Ocean by the MODIS on the Aqua satellite on April 19, 2010. The image reveals both open- and closed-cell cumulus cloud patterns. These cells, or parcels of air, often occur in roughly hexagonal arrays in a layer of fluid (the atmosphere often behaves like a fluid) that begins to "boil," or convect, due to heating at the base or cooling at the top of the layer. In "closed" cells warm air is rising in the center, and sinking around the edges, so clouds appear in cell centers, but evaporate around cell edges. This produces cloud formations like those that dominate the lower left. The reverse flow can also occur: air can sink in the center of the cell and rise at the edge. This process is called "open cell" convection, and clouds form at cell edges around open centers, which creates a lacy, hollow-looking pattern like the clouds in the upper right. Closed and open cell convection represent two stable atmospheric configurations — two sides of the convection coin. But what determines which path the "boiling" atmosphere will take? Apparently the process is highly chaotic, and there appears to be no way to predict whether convection will result in open or closed cells. Indeed, the atmosphere may sometimes flip between one mode and another in no predictable pattern. Satellite: Aqua NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team To learn more about MODIS go to: rapidfire.sci.gsfc.nasa.gov/gallery/?latest NASA Goddard Space Flight Center is home to the nation's largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system, and the universe.

Glory, Vortex Street off Baja California

NASA Technical Reports Server (NTRS)

2007-01-01

On June 19, 2007, the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra satellite captured both a vortex street and a glory visible amid the lattice of clouds over the Pacific Ocean off Baja California. In this image, the swirling clouds known as vortex streets appear along the left edge of the image, stretching southward from Isla Guadalupe. Another NASA satellite captured an earlier example of vortex streets in June 2000. These atmospheric vortices, known as Von Karman vortex streets, often occur in the wake of an obstacle to air flow, such as an island. Stratocumulus clouds--low-lying, sheets of puffy clouds-- over the ocean show the impact of the island on air flow visible though their alternating pattern of clockwise and counter-clockwise swirls. Southeast of the vortex street, a glory, which resembles a rainbow, hovers above the cloud cover. The glory is faint but large, 200 to 300 kilometers long, along a north-south orientation. This phenomenon can occur when the satellite passes directly between the Sun and a bank of clouds below. (People also observe them while looking down on clouds from airplanes.) Not just any kind of cloud can produce a glory; only clouds composed entirely of water droplets (as opposed to ice crystals) can make them. The droplets that form glories generally have diameters of less than 50 micrometers (a micrometers is a millionth of a meter). The water droplets bend the light, showing its different wavelengths, or colors. In this glory, reds and oranges are most visible. NASA image by Jeff Schmaltz, MODIS Rapid Response Team, Goddard Space Flight Center.

Venus Cloud Patterns (colorized and filtered)

NASA Technical Reports Server (NTRS)

1990-01-01

This picture of Venus was taken by the Galileo spacecrafts Solid State Imaging System on February 14, 1990, at a range of almost 1.7 million miles from the planet. A highpass spatial filter has been applied in order to emphasize the smaller scale cloud features, and the rendition has been colorized to a bluish hue in order to emphasize the subtle contrasts in the cloud markings and to indicate that it was taken through a violet filter. The sulfuric acid clouds indicate considerable convective activity, in the equatorial regions of the planet to the left and downwind of the subsolar point (afternoon on Venus). They are analogous to 'fair weather clouds' on Earth. The filamentary dark features visible in the colorized image are here revealed to be composed of several dark nodules, like beads on a string, each about 60 miles across. The Galileo Project is managed for NASA's Office of Space Science and Applications by the Jet Propulsion Laboratory; its mission is to study Jupiter and its satellites and magnetosphere after multiple gravity assist flybys at Venus and Earth. These images of the Venus clouds were taken by Galileo's Solid State Imaging System February 13, 1990, at a range of about 1 million miles. The smallest detail visible is about 20 miles. The two right images show Venus in violet light, the top one at a time six hours later than the bottom one. They show the state of the clouds near the top of Venus's cloud deck. A right to left motion of the cloud features is evident and is consistent with westward winds of about 230 mph. The two left images show Venus in near infrared light, at the same times as the two right images. Sunlight penetrates through the clouds more deeply at the near infrared wavelengths, allowing a view near the bottom of the cloud deck. The westward motion of the clouds is slower (about 150 mph) at the lower altitude. The clouds are composed of sulfuric acid droplets and occupy a range of altitudes from 30 to 45 miles. The images have been spatially filtered to bring out small scale details and de-emphasize global shading. The filtering has introduced artifacts (wiggly lines running north/south) that are faintly visible in the infrared image. The Galileo Project is managed for NASA's Office of Space Science and Applications by the Jet Propulsion Laboratory; its mission is to study Jupiter and its satellites and magnetosphere after multiple gravity assist flybys at Venus and Earth.

A New View on Jupiter's North Pole

NASA Image and Video Library

2018-03-07

This computer-generated image is based on an infrared image of Jupiter's north polar region that was acquired on February 2, 2017, by the Jovian Infrared Auroral Mapper (JIRAM) instrument aboard Juno during the spacecraft's fourth pass over Jupiter. The image shows the structure of the cyclonic pattern observed over Jupiter's North pole: a central cyclone surrounded by eight circumpolar cyclones with diameters ranging from 2,500 to 2,900 miles (4,000 to 4,600 kilometers) across. JIRAM is able to collect images in the infrared wavelengths around 5 micrometers (µm) by measuring the intensity of the heat coming out of the planet. The heat from a planet that is radiated into space is called the radiance. This image is an enhancement of the original JIRAM image. In order to give the picture a 3-D shape, the enhancement starts from the idea that where the radiance has its highest value, there are no clouds and JIRAM can see deeper into the atmosphere. Consequently, all the other areas of the image are originally shaded more or less by clouds of different thickness. Then, to create these pictures, the originals have been inverted to give the thicker clouds the whitish color and the third dimension as the clouds we normally see here in the Earth's atmosphere. https://photojournal.jpl.nasa.gov/catalog/PIA22336

Reflective all-sky thermal infrared cloud imager.

PubMed

Redman, Brian J; Shaw, Joseph A; Nugent, Paul W; Clark, R Trevor; Piazzolla, Sabino

2018-04-30

A reflective all-sky imaging system has been built using a long-wave infrared microbolometer camera and a reflective metal sphere. This compact system was developed for measuring spatial and temporal patterns of clouds and their optical depth in support of applications including Earth-space optical communications. The camera is mounted to the side of the reflective sphere to leave the zenith sky unobstructed. The resulting geometric distortion is removed through an angular map derived from a combination of checkerboard-target imaging, geometric ray tracing, and sun-location-based alignment. A tape of high-emissivity material on the side of the reflector acts as a reference that is used to estimate and remove thermal emission from the metal sphere. Once a bias that is under continuing study was removed, sky radiance measurements from the all-sky imager in the 8-14 μm wavelength range agreed to within 0.91 W/(m 2 sr) of measurements from a previously calibrated, lens-based infrared cloud imager over its 110° field of view.

Jupiter's Northern Hemisphere in Violet Light (Time Set 3)

NASA Technical Reports Server (NTRS)

1997-01-01

Mosaic of Jupiter's northern hemisphere between 10 and 50 degrees latitude. Jupiter's atmospheric circulation is dominated by alternating eastward and westward jets from equatorial to polar latitudes. The direction and speed of these jets in part determine the color and texture of the clouds seen in this mosaic. Also visible are several other common Jovian cloud features, including large white ovals, bright spots, dark spots, interacting vortices, and turbulent chaotic systems. The north-south dimension of each of the two interacting vortices in the upper half of the mosaic is about 3500 kilometers. Light at 410 nanometers is affected by the sizes and compositions of cloud particles, as well as the trace chemicals that give Jupiter's clouds their colors. This mosaic shows the features of Jupiter's main visible cloud deck and the hazy cloud layer above it.

North is at the top. The images are projected on a sphere, with features being foreshortened towards the north. The planetary limb runs along the right edge of the mosaic. Cloud patterns appear foreshortened as they approach the limb. The smallest resolved features are tens of kilometers in size. These images were taken on April 3, 1997, at a range of 1.4 million kilometers by the Solid State Imaging system (CCD) on NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

All-sky photogrammetry techniques to georeference a cloud field

NASA Astrophysics Data System (ADS)

Crispel, Pierre; Roberts, Gregory

2018-01-01

In this study, we present a novel method of identifying and geolocalizing cloud field elements from a portable all-sky camera stereo network based on the ground and oriented towards zenith. The methodology is mainly based on stereophotogrammetry which is a 3-D reconstruction technique based on triangulation from corresponding stereo pixels in rectified images. In cases where clouds are horizontally separated, identifying individual positions is performed with segmentation techniques based on hue filtering and contour detection algorithms. Macroscopic cloud field characteristics such as cloud layer base heights and velocity fields are also deduced. In addition, the methodology is fitted to the context of measurement campaigns which impose simplicity of implementation, auto-calibration, and portability. Camera internal geometry models are achieved a priori in the laboratory and validated to ensure a certain accuracy in the peripheral parts of the all-sky image. Then, stereophotogrammetry with dense 3-D reconstruction is applied with cameras spaced 150 m apart for two validation cases. The first validation case is carried out with cumulus clouds having a cloud base height at 1500 m a.g.l. The second validation case is carried out with two cloud layers: a cumulus fractus layer with a base height at 1000 m a.g.l. and an altocumulus stratiformis layer with a base height of 2300 m a.g.l. Velocity fields at cloud base are computed by tracking image rectangular patterns through successive shots. The height uncertainty is estimated by comparison with a Vaisala CL31 ceilometer located on the site. The uncertainty on the horizontal coordinates and on the velocity field are theoretically quantified by using the experimental uncertainties of the cloud base height and camera orientation. In the first cumulus case, segmentation of the image is performed to identify individuals clouds in the cloud field and determine the horizontal positions of the cloud centers.

Feeding People's Curiosity: Leveraging the Cloud for Automatic Dissemination of Mars Images

NASA Technical Reports Server (NTRS)

Knight, David; Powell, Mark

2013-01-01

Smartphones and tablets have made wireless computing ubiquitous, and users expect instant, on-demand access to information. The Mars Science Laboratory (MSL) operations software suite, MSL InterfaCE (MSLICE), employs a different back-end image processing architecture compared to that of the Mars Exploration Rovers (MER) in order to better satisfy modern consumer-driven usage patterns and to offer greater server-side flexibility. Cloud services are a centerpiece of the server-side architecture that allows new image data to be delivered automatically to both scientists using MSLICE and the general public through the MSL website (http://mars.jpl.nasa.gov/msl/).

Improved automatic estimation of winds at the cloud top of Venus using superposition of cross-correlation surfaces

NASA Astrophysics Data System (ADS)

Ikegawa, Shinichi; Horinouchi, Takeshi

2016-06-01

Accurate wind observation is a key to study atmospheric dynamics. A new automated cloud tracking method for the dayside of Venus is proposed and evaluated by using the ultraviolet images obtained by the Venus Monitoring Camera onboard the Venus Express orbiter. It uses multiple images obtained successively over a few hours. Cross-correlations are computed from the pair combinations of the images and are superposed to identify cloud advection. It is shown that the superposition improves the accuracy of velocity estimation and significantly reduces false pattern matches that cause large errors. Two methods to evaluate the accuracy of each of the obtained cloud motion vectors are proposed. One relies on the confidence bounds of cross-correlation with consideration of anisotropic cloud morphology. The other relies on the comparison of two independent estimations obtained by separating the successive images into two groups. The two evaluations can be combined to screen the results. It is shown that the accuracy of the screened vectors are very high to the equatorward of 30 degree, while it is relatively low at higher latitudes. Analysis of them supports the previously reported existence of day-to-day large-scale variability at the cloud deck of Venus, and it further suggests smaller-scale features. The product of this study is expected to advance the dynamics of venusian atmosphere.

Great Disturbances

NASA Image and Video Library

2013-01-31

This set of images from NASA Cassini spacecraft shows cloud patterns in a band around Saturn before a monstrous thunder-and-lightning storm erupted and again after the head of the storm had disappeared.

Cloud based emergency health care information service in India.

PubMed

Karthikeyan, N; Sukanesh, R

2012-12-01

A hospital is a health care organization providing patient treatment by expert physicians, surgeons and equipments. A report from a health care accreditation group says that miscommunication between patients and health care providers is the reason for the gap in providing emergency medical care to people in need. In developing countries, illiteracy is the major key root for deaths resulting from uncertain diseases constituting a serious public health problem. Mentally affected, differently abled and unconscious patients can't communicate about their medical history to the medical practitioners. Also, Medical practitioners can't edit or view DICOM images instantly. Our aim is to provide palm vein pattern recognition based medical record retrieval system, using cloud computing for the above mentioned people. Distributed computing technology is coming in the new forms as Grid computing and Cloud computing. These new forms are assured to bring Information Technology (IT) as a service. In this paper, we have described how these new forms of distributed computing will be helpful for modern health care industries. Cloud Computing is germinating its benefit to industrial sectors especially in medical scenarios. In Cloud Computing, IT-related capabilities and resources are provided as services, via the distributed computing on-demand. This paper is concerned with sprouting software as a service (SaaS) by means of Cloud computing with an aim to bring emergency health care sector in an umbrella with physical secured patient records. In framing the emergency healthcare treatment, the crucial thing considered necessary to decide about patients is their previous health conduct records. Thus a ubiquitous access to appropriate records is essential. Palm vein pattern recognition promises a secured patient record access. Likewise our paper reveals an efficient means to view, edit or transfer the DICOM images instantly which was a challenging task for medical practitioners in the past years. We have developed two services for health care. 1. Cloud based Palm vein recognition system 2. Distributed Medical image processing tools for medical practitioners.

PIA07600

NASA Image and Video Library

2005-10-04

During its time in orbit, Cassini has spotted many beautiful cat's eye-shaped patterns like the ones visible here. These patterns occur in places where the winds and the atmospheric density at one latitude are different from those at another latitude. The opposing east-west flowing cloud bands are the dominant patterns seen here and elsewhere in Saturn's atmosphere. Contrast in the image was enhanced to aid the visibility of atmospheric features. The image was taken with the Cassini spacecraft wide-angle camera on Aug. 20, 2005. http://photojournal.jpl.nasa.gov/catalog/PIA07600

Filling of Cloud-Induced Gaps for Land Use and Land Cover Classifications Around Refugee Camps

NASA Astrophysics Data System (ADS)

Braun, Andreas; Hagensieker, Ron; Hochschild, Volker

2016-08-01

Clouds cover is one of the main constraints in the field of optical remote sensing. Especially the use of multispectral imagery is affected by either fully obscured data or parts of the image which remain unusable. This study compares four algorithms for the filling of cloud induced gaps in classified land cover products based on Markov Random Fields (MRF), Random Forest (RF), Closest Spectral Fit (CSF) operators. They are tested on a classified image of Sentinel-2 where artificial clouds are filled by information derived from a scene of Sentinel-1. The approaches rely on different mathematical principles and therefore produced results varying in both pattern and quality. Overall accuracies for the filled areas range from 57 to 64 %. Best results are achieved by CSF, however some classes (e.g. sands and grassland) remain critical through all approaches.

Study of atmospheric diffusion using LANDSAT

NASA Technical Reports Server (NTRS)

Torsani, J. A.; Viswanadham, Y.

1982-01-01

The parameters of diffusion patterns of atmospheric pollutants under different conditions were investigated for use in the Gaussian model for calculation of pollution concentration. Value for the divergence pattern of concentration distribution along the Y axis were determined using LANDSAT images. Multispectral scanner images of a point source plume having known characteristics, wind and temperature data, and cloud cover and solar elevation data provided by LANDSAT, were analyzed using the 1-100 system for image analysis. These measured values are compared with pollution transport as predicted by the Pasquill-Gifford, Juelich, and Hoegstroem atmospheric models.

Jupiter's Equatorial Region in a Methane band (Time set 3)

NASA Technical Reports Server (NTRS)

1997-01-01

Mosaic of Jupiter's equatorial region at 727 nanometers (nm). The mosaic covers an area of 34,000 kilometers by 22,000 kilometers. Light at 727 nm is moderately absorbed by atmospheric methane. This image shows the features of Jupiter's main visible cloud deck and upper-tropospheric haze, with higher features enhanced in brightness over lower features. The dark region near the center of the mosaic is an equatorial 'hotspot' similar to the Galileo Probe entry site. These features are holes in the bright, reflective, equatorial cloud layer where warmer thermal emission from Jupiter's deep atmosphere can pass through. The circulation patterns observed here along with the composition measurements from the Galileo Probe suggest that dry air may be converging and sinking over these regions, maintaining their cloud-free appearance. The bright oval in the upper right of the mosaic as well as the other smaller bright features are examples of upwelling of moist air and condensation.

North is at the top. The mosaic covers latitudes 1 to 19 degrees and is centered at longitude 336 degrees West. The planetary limb runs along the right edge of the image. Cloud patterns appear foreshortened as they approach the limb. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers by the Solid State Imaging system aboard NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Jupiter's Northern Hemisphere in a Methane Band (Time Set 3)

NASA Technical Reports Server (NTRS)

1997-01-01

Mosaic of Jupiter's northern hemisphere between 10 and 50 degrees latitude. Jupiter's atmospheric circulation is dominated by alternating eastward and westward jets from equatorial to polar latitudes. The direction and speed of these jets in part determine the color and texture of the clouds seen in this mosaic. Also visible are several other common Jovian cloud features, including large white ovals, bright spots, dark spots, interacting vortices, and turbulent chaotic systems. The north-south dimension of each of the two interacting vortices in the upper half of the mosaic is about 3500 kilometers.

Light at 889 nanometers is strongly absorbed by atmospheric methane. This mosaic shows the features of a hazy cloud layer tens of kilometers above Jupiter's main visible cloud deck. This haze varies in height but appears to be present over the entire region. Small patches of very bright clouds may be similar to terrestrial thunderstorms.

North is at the top. The images are projected on a sphere, with features being foreshortened towards the north. The planetary limb runs along the right edge of the mosaic. Cloud patterns appear foreshortened as they approach the limb. The smallest resolved features are tens of kilometers in size. These images were taken on April 3, 1997, at a range of 1.4 million kilometers by the Solid State Imaging system (CCD) on NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Looking at Earth from Space: Teacher's Guide with Activities for Earth and Space Science

NASA Technical Reports Server (NTRS)

Steele, Colleen (Editor); Steele, Colleen; Ryan, William F.

1995-01-01

The Maryland Pilot Earth Science and Technology Education Network (MAPS-NET) project was sponsored by the National Aeronautics and Space Administration (NASA) to enrich teacher preparation and classroom learning in the area of Earth system science. This publication includes a teacher's guide that replicates material taught during a graduate-level course of the project and activities developed by the teachers. The publication was developed to provide teachers with a comprehensive approach to using satellite imagery to enhance science education. The teacher's guide is divided into topical chapters and enables teachers to expand their knowledge of the atmosphere, common weather patterns, and remote sensing. Topics include: weather systems and satellite imagery including mid-latitude weather systems; wave motion and the general circulation; cyclonic disturbances and baroclinic instability; clouds; additional common weather patterns; satellite images and the internet; environmental satellites; orbits; and ground station set-up. Activities are listed by suggested grade level and include the following topics: using weather symbols; forecasting the weather; cloud families and identification; classification of cloud types through infrared Automatic Picture Transmission (APT) imagery; comparison of visible and infrared imagery; cold fronts; to ski or not to ski (imagery as a decision making tool), infrared and visible satellite images; thunderstorms; looping satellite images; hurricanes; intertropical convergence zone; and using weather satellite images to enhance a study of the Chesapeake Bay. A list of resources is also included.

Reflective all-sky thermal infrared cloud imager

DOE Office of Scientific and Technical Information (OSTI.GOV)

Redman, Brian J.; Shaw, Joseph A.; Nugent, Paul W.

A reflective all-sky imaging system has been built using a long-wave infrared microbolometer camera and a reflective metal sphere. This compact system was developed for measuring spatial and temporal patterns of clouds and their optical depth in support of applications including Earth-space optical communications. The camera is mounted to the side of the reflective sphere to leave the zenith sky unobstructed. The resulting geometric distortion is removed through an angular map derived from a combination of checkerboard-target imaging, geometric ray tracing, and sun-location-based alignment. A tape of high-emissivity material on the side of the reflector acts as a reference thatmore » is used to estimate and remove thermal emission from the metal sphere. In conclusion, once a bias that is under continuing study was removed, sky radiance measurements from the all-sky imager in the 8-14 μm wavelength range agreed to within 0.91 W/(m 2 sr) of measurements from a previously calibrated, lens-based infrared cloud imager over its 110° field of view.« less

Reflective all-sky thermal infrared cloud imager

DOE PAGES

Redman, Brian J.; Shaw, Joseph A.; Nugent, Paul W.; ...

2018-04-17

A reflective all-sky imaging system has been built using a long-wave infrared microbolometer camera and a reflective metal sphere. This compact system was developed for measuring spatial and temporal patterns of clouds and their optical depth in support of applications including Earth-space optical communications. The camera is mounted to the side of the reflective sphere to leave the zenith sky unobstructed. The resulting geometric distortion is removed through an angular map derived from a combination of checkerboard-target imaging, geometric ray tracing, and sun-location-based alignment. A tape of high-emissivity material on the side of the reflector acts as a reference thatmore » is used to estimate and remove thermal emission from the metal sphere. In conclusion, once a bias that is under continuing study was removed, sky radiance measurements from the all-sky imager in the 8-14 μm wavelength range agreed to within 0.91 W/(m 2 sr) of measurements from a previously calibrated, lens-based infrared cloud imager over its 110° field of view.« less

Mars Daily Global Image from April 1999

NASA Image and Video Library

2000-09-08

Twelve orbits a day provide NASA Mars Global Surveyor MOC wide angle cameras a global napshot of weather patterns across the planet. Here, bluish-white water ice clouds hang above the Tharsis volcanoes.

Titan Mystery Clouds

NASA Image and Video Library

2016-12-21

This comparison of two views from NASA's Cassini spacecraft, taken fairly close together in time, illustrates a peculiar mystery: Why would clouds on Saturn's moon Titan be visible in some images, but not in others? In the top view, a near-infrared image from Cassini's imaging cameras, the skies above Saturn's moon Titan look relatively cloud free. But in the bottom view, at longer infrared wavelengths, Cassini sees a large field of bright clouds. Even though these views were taken at different wavelengths, researchers would expect at least a hint of the clouds to show up in the upper image. Thus they have been trying to understand what's behind the difference. As northern summer approaches on Titan, atmospheric models have predicted that clouds will become more common at high northern latitudes, similar to what was observed at high southern latitudes during Titan's late southern summer in 2004. Cassini's Imaging Science Subsystem (ISS) and Visual and Infrared Mapping Spectrometer (VIMS) teams have been observing Titan to document changes in weather patterns as the seasons change, and there is particular interest in following the onset of clouds in the north polar region where Titan's lakes and seas are concentrated. Cassini's "T120" and "T121" flybys of Titan, on June 7 and July 25, 2016, respectively, provided views of high northern latitudes over extended time periods -- more than 24 hours during both flybys. Intriguingly, the ISS and VIMS observations appear strikingly different from each other. In the ISS observations (monochrome image at top), surface features are easily identifiable and only a few small, isolated clouds were detected. In contrast, the VIMS observations (color image at bottom) suggest widespread cloud cover during both flybys. The observations were made over the same time period, so differences in illumination geometry or changes in the clouds themselves are unlikely to be the cause for the apparent discrepancy: VIMS shows persistent atmospheric features over the entire observation period and ISS consistently detects surface features with just a few localized clouds. The answer to what could be causing the discrepancy appears to lie with Titan's hazy atmosphere, which is much easier to see through at the longer infrared wavelengths that VIMS is sensitive to (up to 5 microns) than at the shorter, near-infrared wavelength used by ISS to image Titan's surface and lower atmosphere (0.94 microns). High, thin cirrus clouds that are optically thicker than the atmospheric haze at longer wavelengths, but optically thinner than the haze at the shorter wavelength of the ISS observations, could be detected by VIMS and simultaneously lost in the haze to ISS -- similar to trying to see a thin cloud layer on a hazy day on Earth. This phenomenon has not been seen again since July 2016, but Cassini has several more opportunities to observe Titan over the last months of the mission in 2017, and scientists will be watching to see if and how the weather changes. These two images were taken as part of the T120 flyby on June 7 (VIMS) and 8 (ISS), 2016. The distance to Titan was about 28,000 miles (45,000 kilometers) for the VIMS image and about 398,000 miles (640,000 kilometers) for the ISS image. The VIMS image has been processed to enhance the visibility of the clouds; in this false-color view, clouds appear nearly white, atmospheric haze is pink, and surface areas would appear green. http://photojournal.jpl.nasa.gov/catalog/PIA21054

Earth Observation taken by the Expedition 20 crew

NASA Image and Video Library

2009-10-06

ISS020-E-047807 (6 Oct. 2009) --- Thunderstorms on the Brazilian horizon are featured in this image photographed by an Expedition 20 crew member on the International Space Station. A picturesque line of thunderstorms and numerous circular cloud patterns filled the view as the station crew members looked out at the limb and atmosphere (blue line on the horizon) of Earth. This region displayed in the photograph (top) includes an unstable, active atmosphere forming a large area of cumulonimbus clouds in various stages of development. The crew was looking west southwestward from the Amazon Basin, along the Rio Madeira, toward Bolivia when the image was taken. The distinctive circular patterns of the clouds in this view are likely caused by the aging of thunderstorms. Such ring structures often form during the final stages of a storm?s development as their centers collapse. Sunglint is visible on the waters of the Rio Madeira and Lago Acara in the Amazon Basin. Widespread haze over the basin gives the reflected light an orange hue. The Rio Madeira flows northward and joins the Amazon River on its path to the Atlantic Ocean. Scientists believe that a large smoke plume near the bottom center of the image may explain one source of the haze.

The influence of surface roughness on cloud cavitation flow around hydrofoils

NASA Astrophysics Data System (ADS)

Hao, Jiafeng; Zhang, Mindi; Huang, Xu

2018-02-01

The aim of this study is to investigate experimentally the effect of surface roughness on cloud cavitation around Clark-Y hydrofoils. High-speed video and particle image velocimetry (PIV) were used to obtain cavitation patterns images (Prog. Aerosp. Sci. 37: 551-581, 2001), as well as velocity and vorticity fields. Results are presented for cloud cavitating conditions around a Clark-Y hydrofoil fixed at angle of attack of α =8{°} for moderate Reynolds number of Re=5.6 × 105. The results show that roughness had a great influence on the pattern, velocity and vorticity distribution of cloud cavitation. For cavitating flow around a smooth hydrofoil (A) and a rough hydrofoil (B), cloud cavitation occurred in the form of finger-like cavities and attached subulate cavities, respectively. The period of cloud cavitation around hydrofoil A was shorter than for hydrofoil B. Surface roughness had a great influence on the process of cloud cavitation. The development of cloud cavitation around hydrofoil A consisted of two stages: (1) Attached cavities developed along the surface to the trailing edge; (2) A reentrant jet developed, resulting in shedding and collapse of cluster bubbles or vortex structure. Meanwhile, its development for hydrofoil B included three stages: (1) Attached cavities developed along the surface to the trailing edge, with accumulation and rotation of bubbles at the trailing edge of the hydrofoil affecting the flow field; (2) Development of a reentrant jet resulted in the first shedding of cavities. Interaction and movement of flows from the pressure side and suction side brought liquid water from the pressure side to the suction side of the hydrofoil, finally forming a reentrant jet. The jet kept moving along the surface to the leading edge of the hydrofoil, resulting in large-scale shedding of cloud bubbles. Several vortices appeared and dissipated during the process; (3) Cavities grew and shed again.

A one year Landsat 8 conterminous United States study of spatial and temporal patterns of cirrus and non-cirrus clouds and implications for the long term Landsat archive.

NASA Astrophysics Data System (ADS)

Kovalskyy, V.; Roy, D. P.

2014-12-01

The successful February 2013 launch of the Landsat 8 satellite is continuing the 40+ year legacy of the Landsat mission. The payload includes the Operational Land Imager (OLI) that has a new 1370 mm band designed to monitor cirrus clouds and the Thermal Infrared Sensor (TIRS) that together provide 30m low, medium and high confidence cloud detections and 30m low and high confidence cirrus cloud detections. A year of Landsat 8 data over the Conterminous United States (CONUS), composed of 11,296 acquisitions, was analyzed comparing the spatial and temporal incidence of these cloud and cirrus states. This revealed (i) 36.5% of observations were detected with high confidence cloud with spatio-temporal patterns similar to those observed by previous Landsat 7 cloud analyses, (ii) 29.2% were high confidence cirrus, (iii) 20.9% were both high confidence cloud and high confidence cirrus, (iv) 8.3% were detected as high confidence cirrus but not as high confidence cloud. The results illustrate the value of the cirrus band for improved Landsat 8 terrestrial monitoring but imply that the historical CONUS Landsat archive has a similar 8% of undetected cirrus contaminated pixels. The implications for long term Landsat time series records, including the global Web Enabled Landsat Data (WELD) product record, are discussed.

Three dimensional Visualization of Jupiter's Equatorial Region

NASA Technical Reports Server (NTRS)

1997-01-01

Frames from a three dimensional visualization of Jupiter's equatorial region. The images used cover an area of 34,000 kilometers by 11,000 kilometers (about 21,100 by 6,800 miles) near an equatorial 'hotspot' similar to the site where the probe from NASA's Galileo spacecraft entered Jupiter's atmosphere on December 7th, 1995. These features are holes in the bright, reflective, equatorial cloud layer where warmer thermal emission from Jupiter's deep atmosphere can pass through. The circulation patterns observed here along with the composition measurements from the Galileo Probe suggest that dry air may be converging and sinking over these regions, maintaining their cloud-free appearance. The bright clouds to the right of the hotspot as well as the other bright features may be examples of upwelling of moist air and condensation.

This frame is a view to the northeast, from between the cloud layers and above the streaks in the lower cloud leading towards the hotspot. The upper haze layer has some features that match the lower cloud, such as the bright streak in the foreground of the frame. These are probably thick clouds that span several tens of vertical kilometers.

Galileo is the first spacecraft to image Jupiter in near-infrared light (which is invisible to the human eye) using three filters at 727, 756, and 889 nanometers (nm). Because light at these three wavelengths is absorbed at different altitudes by atmospheric methane, a comparison of the resulting images reveals information about the heights of clouds in Jupiter's atmosphere. This information can be visualized by rendering cloud surfaces with the appropriate height variations.

The visualization reduces Jupiter's true cloud structure to two layers. The height of a high haze layer is assumed to be proportional to the reflectivity of Jupiter at 889 nm. The height of a lower tropospheric cloud is assumed to be proportional to the reflectivity at 727 nm divided by that at 756 nm. This model is overly simplistic, but is based on more sophisticated studies of Jupiter's cloud structure. The upper and lower clouds are separated in the rendering by an arbitrary amount, and the height variations are exaggerated by a factor of 25.

The lower cloud is colored using the same false color scheme used in previously released image products, assigning red, green, and blue to the 756, 727, and 889 nanometer mosaics, respectively. Light bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the lower cloud with an overlying thin haze.

The images used cover latitudes 1 to 10 degrees and are centered at longitude 336 degrees west. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers (about 930,000 miles) by the Solid State Imaging (CCD) system on NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the Galileo mission for NASA's Office of Space Science, Washington, DC. JPL is an operating division of California Institute of Technology (Caltech).

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://www.jpl.nasa.gov/ galileo.

Three dimensional Visualization of Jupiter's Equatorial Region

NASA Technical Reports Server (NTRS)

1997-01-01

Frames from a three dimensional visualization of Jupiter's equatorial region. The images used cover an area of 34,000 kilometers by 11,000 kilometers (about 21,100 by 6,800 miles) near an equatorial 'hotspot' similar to the site where the probe from NASA's Galileo spacecraft entered Jupiter's atmosphere on December 7th, 1995. These features are holes in the bright, reflective, equatorial cloud layer where warmer thermal emission from Jupiter's deep atmosphere can pass through. The circulation patterns observed here along with the composition measurements from the Galileo Probe suggest that dry air may be converging and sinking over these regions, maintaining their cloud-free appearance. The bright clouds to the right of the hotspot as well as the other bright features may be examples of upwelling of moist air and condensation.

This frame is a view to the northeast, from between the cloud layers and above the streaks in the lower cloud leading towards the hotspot. The hotspot is clearly visible as a deep blue feature. The cloud streaks end near the hotspot, consistent with the idea that clouds traveling along these streak lines descend and evaporate as they approach the hotspot. The upper haze layer is slightly bowed upwards above the hotspot.

Galileo is the first spacecraft to image Jupiter in near-infrared light (which is invisible to the human eye) using three filters at 727, 756, and 889 nanometers (nm). Because light at these three wavelengths is absorbed at different altitudes by atmospheric methane, a comparison of the resulting images reveals information about the heights of clouds in Jupiter's atmosphere. This information can be visualized by rendering cloud surfaces with the appropriate height variations.

The visualization reduces Jupiter's true cloud structure to two layers. The height of a high haze layer is assumed to be proportional to the reflectivity of Jupiter at 889 nm. The height of a lower tropospheric cloud is assumed to be proportional to the reflectivity at 727 nm divided by that at 756 nm. This model is overly simplistic, but is based on more sophisticated studies of Jupiter's cloud structure. The upper and lower clouds are separated in the rendering by an arbitrary amount, and the height variations are exaggerated by a factor of 25.

The lower cloud is colored using the same false color scheme used in previously released image products, assigning red, green, and blue to the 756, 727, and 889 nanometer mosaics, respectively. Light bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the lower cloud with an overlying thin haze.

The images used cover latitudes 1 to 10 degrees and are centered at longitude 336 degrees west. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers (about 930,000 miles) by the Solid State Imaging (CCD) system on NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the Galileo mission for NASA's Office of Space Science, Washington, DC. JPL is an operating division of California Institute of Technology (Caltech).

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://www.jpl.nasa.gov/ galileo.

Ship-wave-shaped wave clouds induced by Kuril Islands

NASA Image and Video Library

2015-06-09

The Kuril Islands are a string of volcanically-formed islands that stretch between Russia and Japan, separating the North Pacific Ocean from the Sea of Okhotsk. Subject to the cold, moist breezes from the North Atlantic, and the frigid air from Siberia, the climate is severe, with frequent storms, and ever-present winds, which often reach hurricane strength. Cloudy, windy conditions are common. On June 1, 2015 the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA’s Aqua satellite captured this true-color image as it passed over the Kuril Islands. Clouds curl into the center of a storm system, bringing strong winds to the region. As the winds scrape over the tall volcanic peaks of the Kuril Islands, they become turbulent air behind the islands. The turbulence disturbs the cloudbank, etching its passage into a striking pattern that can be seen from space. This particular pattern is called “ship-waved-shaped wave clouds”, because the pattern can be likened to that formed behind a ship cutting through a smooth ocean. On the windward side of the Kuril Islands, the cloud bank is generally smooth, with streaks that are lined up parallel to the movement of the wind, blowing from the west and towards the east. Behind the tall volcanic peaks of the islands, V’s fan out on the leeward side, illustrating the flow of the turbulent air. Image Credit: Jeff Schmaltz, MODIS Land Rapid Response Team, NASA GSFC NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Stationary waves and slowly moving features in the night upper clouds of Venus

NASA Astrophysics Data System (ADS)

Peralta, J.; Hueso, R.; Sánchez-Lavega, A.; Lee, Y. J.; Muñoz, A. García; Kouyama, T.; Sagawa, H.; Sato, T. M.; Piccioni, G.; Tellmann, S.; Imamura, T.; Satoh, T.

2017-08-01

At the cloud top level of Venus (65-70 km altitude) the atmosphere rotates 60 times faster than the underlying surface—a phenomenon known as superrotation1,2. Whereas on Venus's dayside the cloud top motions are well determined3,4,5,6 and Venus general circulation models predict the mean zonal flow at the upper clouds to be similar on both the day and nightside2, the nightside circulation remains poorly studied except for the polar region7,8. Here, we report global measurements of the nightside circulation at the upper cloud level. We tracked individual features in thermal emission images at 3.8 and 5.0 μm obtained between 2006 and 2008 by the Visible and Infrared Thermal Imaging Spectrometer-Mapper onboard Venus Express and in 2015 by ground-based measurements with the Medium-Resolution 0.8-5.5 Micron Spectrograph and Imager at the National Aeronautics and Space Administration Infrared Telescope Facility. The zonal motions range from -110 to -60 m s-1, which is consistent with those found for the dayside but with larger dispersion6. Slow motions (-50 to -20 m s-1) were also found and remain unexplained. In addition, abundant stationary wave patterns with zonal speeds from -10 to +10 m s-1 dominate the night upper clouds and concentrate over the regions of higher surface elevation.

Wave clouds over the Central African Republic

NASA Image and Video Library

2016-02-04

On January 27, 2016, the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA’s Aqua satellite passed over the Central African Republic and captured a true-color image of wave clouds rippling over a fire-speckled landscape. Wave clouds typically form when a mountain, island, or even another mass of air forces an air mass to rise, then fall again, in a wave pattern. The air cools as it rises, and if there is moisture in the air, the water condenses into clouds at the top of the wave. As the air begins to sink, the air warms and the cloud dissipates. The result is a line of clouds marking the crests of the wave separated by clear areas in the troughs of the wave. In addition to the long lines of clouds stretching across the central section of the country, clouds appear to line up in parallel rows near the border of the Democratic Republic of the Congo. In this area, small sets of grayish cloud appear to be lined up with the prevailing wind, judging by the plumes of smoke rising from red hotspots near each set of clouds. Clouds like this, that line in parallel rows parallel with the prevailing wind, are known as “cloud streets”. Each red “hotspot” marks an area where the thermal sensors on the MODIS instrument detected high temperatures. When accompanied by typical smoke, such hotspots are diagnostic for actively burning fires. Given the time of the year, the widespread nature, and the location of the fires, they are almost certainly agricultural fires that have been deliberately set to manage land. Image Credit: Jeff Schmaltz, MODIS Land Rapid Response Team, NASA GSFC NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Extratropical Cyclone in the Southern Ocean

NASA Technical Reports Server (NTRS)

2002-01-01

These images from the Multi-angle Imaging SpectroRadiometer (MISR) portray an occluded extratropical cyclone situated in the Southern Ocean, about 650 kilometers south of the Eyre Peninsula, South Australia. The left-hand image, a true-color view from MISR's nadir (vertical-viewing) camera, shows clouds just south of the Yorke Peninsula and the Murray-Darling river basin in Australia. Retrieved cloud-tracked wind velocities are indicated by the superimposed arrows. The image on the right displays cloud-top heights. Areas where cloud heights could not be retrieved are shown in black. Both the wind vectors and the cloud heights were derived using data from multiple MISR cameras within automated computer processing algorithms. The stereoscopic algorithms used to generate these results are still being refined, and future versions of these products may show modest changes. Extratropical cyclones are the dominant weather system at midlatitudes, and the term is used generically for regional low-pressure systems in the mid- to high-latitudes. In the southern hemisphere, cyclonic rotation is clockwise. These storms obtain their energy from temperature differences between air masses on either side of warm and cold fronts, and their characteristic pattern is of warm and cold fronts radiating out from a migrating low pressure center which forms, deepens, and dissipates as the fronts fold and collapse on each other. The center of this cyclone has started to decay, with the band of cloud to the south most likely representing the main front that was originally connected with the cyclonic circulation. These views were acquired on October 11, 2001, and the large view represents an area of about 380 kilometers x 1900 kilometers. Image courtesy NASA/GSFC/LaRC/JPL, MISR Team.

Jupiter Equatorial Region in a Methane Band Time Set 1

NASA Image and Video Library

1998-03-06

Mosaic of an equatorial "hotspot" on Jupiter at 889 nanometers (nm). The mosaic covers an area of 34,000 kilometers by 11,000 kilometers. Light at 889 nm is strongly absorbed by atmospheric methane. This image shows the features of a hazy cloud layer tens of kilometers above Jupiter's main visible cloud deck. This haze varies in height but appears to be present over the entire region. Small patches of very bright clouds may be similar to terrestrial thunderstorms. The dark region near the center of the mosaic is an equatorial "hotspot" similar to the Galileo Probe entry site. These features are holes in the bright, reflective, equatorial cloud layer where warmer thermal emission from Jupiter's deep atmosphere can pass through. The circulation patterns observed here along with the composition measurements from the Galileo Probe suggest that dry air may be converging and sinking over these regions, maintaining their cloud-free appearance. North is at the top. The mosaic covers latitudes 1 to 10 degrees and is centered at longitude 336 degrees West. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers by the Solid State Imaging system aboard NASA's Galileo spacecraft. http://photojournal.jpl.nasa.gov/catalog/PIA01200

The Cloud Top Distribution and Diurnal Variation of Clouds Over East Asia: Preliminary Results From Advanced Himawari Imager

NASA Astrophysics Data System (ADS)

Chen, Dandan; Guo, Jianping; Wang, Hongqing; Li, Jian; Min, Min; Zhao, Wenhui; Yao, Dan

2018-04-01

Clouds, as one of the most uncertain factors in climate system, have been intensively studied as satellites with advanced instruments emerged in recent years. However, few studies examine the vertical distributions of cloud top and their temporal variations over East Asia based on geostationary satellite data. In this study, the vertical structures of cloud top and its diurnal variations in summer of 2016 are analyzed using the Advanced Himawari Imager/Himawari-8 cloud products. Results show that clouds occur most frequently over the southern Tibetan Plateau and the Bay of Bengal. We find a steep gradient of cloud occurrence frequency extending from southwest to northeast China and low-value centers over the eastern Pacific and the Inner Mongolia Plateau. The vertical structures of cloud top are highly dependent on latitude, in addition to the nonnegligible roles of both terrain and land-sea thermal contrast. In terms of the diurnal cycle, clouds tend to occur more often in the afternoon, peaking around 1700 local time over land and ocean. The amplitude of cloud diurnal variation over ocean is much smaller than that over land, and complex terrain tends to be linked to larger amplitude. In vertical, the diurnal cycle of cloud frequency exhibits bimodal pattern over both land and ocean. The high-level peaks occur at almost the same altitude over land and ocean. In contrast, the low-level peaks over ocean mainly reside in the boundary layer, much lower than those over land, which could be indicative of the frequent occurrence of marine boundary layer clouds.

Three dimensional Visualization of Jupiter's Equatorial Region

NASA Technical Reports Server (NTRS)

1997-01-01

Frames from a three dimensional visualization of Jupiter's equatorial region. The images used cover an area of 34,000 kilometers by 11,000 kilometers (about 21,100 by 6,800 miles) near an equatorial 'hotspot' similar to the site where the probe from NASA's Galileo spacecraft entered Jupiter's atmosphere on December 7th, 1995. These features are holes in the bright, reflective, equatorial cloud layer where warmer thermal emission from Jupiter's deep atmosphere can pass through. The circulation patterns observed here along with the composition measurements from the Galileo Probe suggest that dry air may be converging and sinking over these regions, maintaining their cloud-free appearance. The bright clouds to the right of the hotspot as well as the other bright features may be examples of upwelling of moist air and condensation.

This frame is a view from the southwest looking northeast, from an altitude just above the high haze layer. The streaks in the lower cloud leading towards the hotspot are visible. The upper haze layer is mostly flat, with notable small peaks that can be matched with features in the lower cloud. In reality, these areas may represent a continuous vertical cloud column.

Galileo is the first spacecraft to image Jupiter in near-infrared light (which is invisible to the human eye) using three filters at 727, 756, and 889 nanometers (nm). Because light at these three wavelengths is absorbed at different altitudes by atmospheric methane, a comparison of the resulting images reveals information about the heights of clouds in Jupiter's atmosphere. This information can be visualized by rendering cloud surfaces with the appropriate height variations.

The visualization reduces Jupiter's true cloud structure to two layers. The height of a high haze layer is assumed to be proportional to the reflectivity of Jupiter at 889 nm. The height of a lower tropospheric cloud is assumed to be proportional to the reflectivity at 727 nm divided by that at 756 nm. This model is overly simplistic, but is based on more sophisticated studies of Jupiter's cloud structure. The upper and lower clouds are separated in the rendering by an arbitrary amount, and the height variations are exaggerated by a factor of 25.

The lower cloud is colored using the same false color scheme used in previously released image products, assigning red, green, and blue to the 756, 727, and 889 nanometer mosaics, respectively. Light bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the lower cloud with an overlying thin haze.

The images used cover latitudes 1 to 10 degrees and are centered at longitude 336 degrees west. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers (about 930,000 miles) by the Solid State Imaging (CCD) system on NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the Galileo mission for NASA's Office of Space Science, Washington, DC. JPL is an operating division of California Institute of Technology (Caltech).

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov.

Three dimensional Visualization of Jupiter's Equatorial Region

NASA Technical Reports Server (NTRS)

1997-01-01

Frames from a three dimensional visualization of Jupiter's equatorial region. The images used cover an area of 34,000 kilometers by 11,000 kilometers (about 21,100 by 6,800 miles) near an equatorial 'hotspot' similar to the site where the probe from NASA's Galileo spacecraft entered Jupiter's atmosphere on December 7th, 1995. These features are holes in the bright, reflective, equatorial cloud layer where warmer thermal emission from Jupiter's deep atmosphere can pass through. The circulation patterns observed here along with the composition measurements from the Galileo Probe suggest that dry air may be converging and sinking over these regions, maintaining their cloud-free appearance. The bright clouds to the right of the hotspot as well as the other bright features may be examples of upwelling of moist air and condensation.

This frame is a view to the southeast, from between the cloud layers and over the north center of the region. The tall white clouds in the lower cloud deck are probably much like large terrestrial thunderclouds. They may be regions where atmospheric water powers vertical convection over large horizontal distances.

Galileo is the first spacecraft to image Jupiter in near-infrared light (which is invisible to the human eye) using three filters at 727, 756, and 889 nanometers (nm). Because light at these three wavelengths is absorbed at different altitudes by atmospheric methane, a comparison of the resulting images reveals information about the heights of clouds in Jupiter's atmosphere. This information can be visualized by rendering cloud surfaces with the appropriate height variations.

The visualization reduces Jupiter's true cloud structure to two layers. The height of a high haze layer is assumed to be proportional to the reflectivity of Jupiter at 889 nm. The height of a lower tropospheric cloud is assumed to be proportional to the reflectivity at 727 nm divided by that at 756 nm. This model is overly simplistic, but is based on more sophisticated studies of Jupiter's cloud structure. The upper and lower clouds are separated in the rendering by an arbitrary amount, and the height variations are exaggerated by a factor of 25.

The lower cloud is colored using the same false color scheme used in previously released image products, assigning red, green, and blue to the 756, 727, and 889 nanometer mosaics, respectively. Light bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the lower cloud with an overlying thin haze.

The images used cover latitudes 1 to 10 degrees and are centered at longitude 336 degrees west. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers (about 930,000 miles) by the Solid State Imaging (CCD) system on NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the Galileo mission for NASA's Office of Space Science, Washington, DC. JPL is an operating division of California Institute of Technology (Caltech).

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://www.jpl.nasa.gov/ galileo.

Three dimensional Visualization of Jupiter's Equatorial Region

NASA Technical Reports Server (NTRS)

1997-01-01

Frames from a three dimensional visualization of Jupiter's equatorial region. The images used cover an area of 34,000 kilometers by 11,000 kilometers (about 21,100 by 6,800 miles) near an equatorial 'hotspot' similar to the site where the probe from NASA's Galileo spacecraft entered Jupiter's atmosphere on December 7th, 1995. These features are holes in the bright, reflective, equatorial cloud layer where warmer thermal emission from Jupiter's deep atmosphere can pass through. The circulation patterns observed here along with the composition measurements from the Galileo Probe suggest that dry air may be converging and sinking over these regions, maintaining their cloud-free appearance. The bright clouds to the right of the hotspot as well as the other bright features may be examples of upwelling of moist air and condensation.

This frame is a view to the west, from between the cloud layers and over the patchy white clouds to the east of the hotspot. This is probably an area where moist convection is occurring over large horizontal distances, similar to the atmosphere over the equatorial ocean on Earth. The clouds are high and thick, and are observed to change rapidly over short time scales.

Galileo is the first spacecraft to image Jupiter in near-infrared light (which is invisible to the human eye) using three filters at 727, 756, and 889 nanometers (nm). Because light at these three wavelengths is absorbed at different altitudes by atmospheric methane, a comparison of the resulting images reveals information about the heights of clouds in Jupiter's atmosphere. This information can be visualized by rendering cloud surfaces with the appropriate height variations.

The visualization reduces Jupiter's true cloud structure to two layers. The height of a high haze layer is assumed to be proportional to the reflectivity of Jupiter at 889 nm. The height of a lower tropospheric cloud is assumed to be proportional to the reflectivity at 727 nm divided by that at 756 nm. This model is overly simplistic, but is based on more sophisticated studies of Jupiter's cloud structure. The upper and lower clouds are separated in the rendering by an arbitrary amount, and the height variations are exaggerated by a factor of 25.

The lower cloud is colored using the same false color scheme used in previously released image products, assigning red, green, and blue to the 756, 727, and 889 nanometer mosaics, respectively. Light bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the lower cloud with an overlying thin haze.

The images used cover latitudes 1 to 10 degrees and are centered at longitude 336 degrees west. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers (about 930,000 miles) by the Solid State Imaging (CCD) system on NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the Galileo mission for NASA's Office of Space Science, Washington, DC. JPL is an operating division of California Institute of Technology (Caltech).

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov.

The use of ERTS-1 satellite data in Great Lakes mesometeorological studies

NASA Technical Reports Server (NTRS)

Lyons, W. A. (Principal Investigator)

1972-01-01

The author has identified the following significant results. In the original proposal, it was hoped that ERTS could, with its extremely high resolution and multispectral capability, detect many meteorological phenomena occurring at the low end of the mesoscale motion spectrum (1 - 100 km). This included convective cloud phenomena, internal wave patterns, air pollution, snow squalls, etc. For meteorologists, ERTS-1 has more than lived up to initial hopes. First-look inspection of images has produced a large number of truly remarkable finds. Some of the most significant are: (1) Images of Lake Ontario during late summer have revealed several extremely good examples of lake breeze frontal cloud patterns. (2) Detection of suspended particulates from Chicago-Gary industrial complex in the 50,000 to 150,000 tons/year category. (3) Inadvertant weather modification due to anthropogenic condensation and ice nuclei from urban areas.

Wind Patterns in Jupiter's Equatorial Region (Time set 1)

NASA Technical Reports Server (NTRS)

1997-01-01

Wind patterns of Jupiter's equatorial region. This mosaic covers an area of 34,000 kilometers by 22,000 kilometers and was taken using the 756 nanometer (nm) near-infrared continuum filter. The dark region near the center of the mosaic is an equatorial 'hotspot' similar to the Galileo Probe entry site. The near-infrared continuum filter shows the features of Jupiter's main visible cloud deck.

Jupiter's atmospheric circulation is dominated by alternating jets of east/west (zonal) winds. The bands have different widths and wind speeds but have remained constant as long as telescopes and spacecraft have measured them. The top half of these mosaics lies within Jupiter's North Equatorial Belt, a westward (left) current. The bottom half shows part of the Equatorial Zone, a fast moving eastward current. The clouds near the hotspot are the fastest moving features in these mosaics, moving at about 100 meters per second, or 224 miles per hour.

Superimposed on the zonal wind currents is the Jovian 'weather'. The arrows show the winds measured by an observer moving eastward (right) at the speed of the hotspot. (The observer's perspective is that the hotspot is 'still' while the rest of the planet moves around it.) Clouds south of the hotspot appear to be moving towards it, as seen in the flow aligned with cloud streaks to the southwest and in the clockwise flow to the southeast. Interestingly, there is little cloud motion away from the hotspot in any direction. This is consistent with the idea that dry air is converging over this region and sinking, maintaining the cloud-free nature of the hotspot.

North is at the top. The mosaic covers latitudes 1 to 19 degrees and is centered at longitude 336 degrees West. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers by the Solid State Imaging system aboard NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

A compressive sensing based secure watermark detection and privacy preserving storage framework.

PubMed

Qia Wang; Wenjun Zeng; Jun Tian

2014-03-01

Privacy is a critical issue when the data owners outsource data storage or processing to a third party computing service, such as the cloud. In this paper, we identify a cloud computing application scenario that requires simultaneously performing secure watermark detection and privacy preserving multimedia data storage. We then propose a compressive sensing (CS)-based framework using secure multiparty computation (MPC) protocols to address such a requirement. In our framework, the multimedia data and secret watermark pattern are presented to the cloud for secure watermark detection in a CS domain to protect the privacy. During CS transformation, the privacy of the CS matrix and the watermark pattern is protected by the MPC protocols under the semi-honest security model. We derive the expected watermark detection performance in the CS domain, given the target image, watermark pattern, and the size of the CS matrix (but without the CS matrix itself). The correctness of the derived performance has been validated by our experiments. Our theoretical analysis and experimental results show that secure watermark detection in the CS domain is feasible. Our framework can also be extended to other collaborative secure signal processing and data-mining applications in the cloud.

Open-cell and closed-cell clouds off Peru

NASA Image and Video Library

2010-04-27

2010/107 - 04/17 at 21 :05 UTC. Open-cell and closed-cell clouds off Peru, Pacific Ocean Resembling a frosted window on a cold winter's day, this lacy pattern of marine clouds was captured off the coast of Peru in the Pacific Ocean by the MODIS on the Aqua satellite on April 19, 2010. The image reveals both open- and closed-cell cumulus cloud patterns. These cells, or parcels of air, often occur in roughly hexagonal arrays in a layer of fluid (the atmosphere often behaves like a fluid) that begins to "boil," or convect, due to heating at the base or cooling at the top of the layer. In "closed" cells warm air is rising in the center, and sinking around the edges, so clouds appear in cell centers, but evaporate around cell edges. This produces cloud formations like those that dominate the lower left. The reverse flow can also occur: air can sink in the center of the cell and rise at the edge. This process is called "open cell" convection, and clouds form at cell edges around open centers, which creates a lacy, hollow-looking pattern like the clouds in the upper right. Closed and open cell convection represent two stable atmospheric configurations — two sides of the convection coin. But what determines which path the "boiling" atmosphere will take? Apparently the process is highly chaotic, and there appears to be no way to predict whether convection will result in open or closed cells. Indeed, the atmosphere may sometimes flip between one mode and another in no predictable pattern. Satellite: Aqua NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team To learn more about MODIS go to: rapidfire.sci.gsfc.nasa.gov/gallery/?latest NASA Goddard Space Flight Center is home to the nation's largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system, and the universe.

Multi-layer Clouds Over the South Indian Ocean

NASA Technical Reports Server (NTRS)

2003-01-01

The complex structure and beauty of polar clouds are highlighted by these images acquired by the Multi-angle Imaging SpectroRadiometer (MISR) on April 23, 2003. These clouds occur at multiple altitudes and exhibit a noticeable cyclonic circulation over the Southern Indian Ocean, to the north of Enderbyland, East Antarctica.

The image at left was created by overlying a natural-color view from MISR's downward-pointing (nadir) camera with a color-coded stereo height field. MISR retrieves heights by a pattern recognition algorithm that utilizes multiple view angles to derive cloud height and motion. The opacity of the height field was then reduced until the field appears as a translucent wash over the natural-color image. The resulting purple, cyan and green hues of this aesthetic display indicate low, medium or high altitudes, respectively, with heights ranging from less than 2 kilometers (purple) to about 8 kilometers (green). In the lower right corner, the edge of the Antarctic coastline and some sea ice can be seen through some thin, high cirrus clouds.

The right-hand panel is a natural-color image from MISR's 70-degree backward viewing camera. This camera looks backwards along the path of Terra's flight, and in the southern hemisphere the Sun is in front of this camera. This perspective causes the cloud-tops to be brightly outlined by the sun behind them, and enhances the shadows cast by clouds with significant vertical structure. An oblique observation angle also enhances the reflection of light by atmospheric particles, and accentuates the appearance of polar clouds. The dark ocean and sea ice that were apparent through the cirrus clouds at the bottom right corner of the nadir image are overwhelmed by the brightness of these clouds at the oblique view.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 17794. The panels cover an area of 335 kilometers x 605 kilometers, and utilize data from blocks 142 to 145 within World Reference System-2 path 155.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

An Intelligent Cloud Storage Gateway for Medical Imaging.

PubMed

Viana-Ferreira, Carlos; Guerra, António; Silva, João F; Matos, Sérgio; Costa, Carlos

2017-09-01

Historically, medical imaging repositories have been supported by indoor infrastructures. However, the amount of diagnostic imaging procedures has continuously increased over the last decades, imposing several challenges associated with the storage volume, data redundancy and availability. Cloud platforms are focused on delivering hardware and software services over the Internet, becoming an appealing solution for repository outsourcing. Although this option may bring financial and technological benefits, it also presents new challenges. In medical imaging scenarios, communication latency is a critical issue that still hinders the adoption of this paradigm. This paper proposes an intelligent Cloud storage gateway that optimizes data access times. This is achieved through a new cache architecture that combines static rules and pattern recognition for eviction and prefetching. The evaluation results, obtained from experiments over a real-world dataset, show that cache hit ratios can reach around 80%, leading to reductions of image retrieval times by over 60%. The combined use of eviction and prefetching policies proposed can significantly reduce communication latency, even when using a small cache in comparison to the total size of the repository. Apart from the performance gains, the proposed system is capable of adjusting to specific workflows of different institutions.

Jupiter's Equatorial Region in a Methane band (Time set 1)

NASA Technical Reports Server (NTRS)

1997-01-01

Mosaic of an equatorial 'hotspot' on Jupiter at 889 nanometers (nm). The mosaic covers an area of 34,000 kilometers by 11,000 kilometers. Light at 889 nm is strongly absorbed by atmospheric methane. This image shows the features of a hazy cloud layer tens of kilometers above Jupiter's main visible cloud deck. This haze varies in height but appears to be present over the entire region. Small patches of very bright clouds may be similar to terrestrial thunderstorms. The dark region near the center of the mosaic is an equatorial 'hotspot' similar to the Galileo Probe entry site. These features are holes in the bright, reflective, equatorial cloud layer where warmer thermal emission from Jupiter's deep atmosphere can pass through. The circulation patterns observed here along with the composition measurements from the Galileo Probe suggest that dry air may be converging and sinking over these regions, maintaining their cloud-free appearance.

North is at the top. The mosaic covers latitudes 1 to 10 degrees and is centered at longitude 336 degrees West. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers by the Solid State Imaging system aboard NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Analysis of rainfall over northern Peru during El Nino: A PCDS application

NASA Technical Reports Server (NTRS)

Goldberg, R.; Tisnado, G.

1986-01-01

In an examination of GOES satellite data during the 1982 through 1983 El Nino period, the appearance of lee wave cloud patterns was revealed. A correlation was hypothesized relating an anomalous easterly flow across the Andes with the appearance of these wave patterns and with the subsequent onset of intense rainfall. The cloud patterns are belived to be associated with the El Nino period and could be viewed as precursors to significant changes in weather patterns. The ultimate goal of the researchers will be the ability to predict occurrences of rainstorms associated with the appearance of lee waves and related cloud patterns as harbingers of destruction caused by flooding, huaycos, and other catastrophic consequences of heavy and abnormal rainfall. Rainfall data from about 70 stations in northern Peru from 1980 through 1984 were formatted to be utilized within the Pilot Climate Data System (PCDS). This time period includes the 1982 through 1983 El Nino period. As an example of the approach, a well-pronounced lee wave pattern was shown from a GOES satellite image of April 4, 1983. The ground truth data were then displayed via the PCDS to graphically demonstrate the increase in intensity and areal distribution of rainfall in the northern Peruvian area in the next 4 to 5 days.

Earth Observations taken by the Expedition 15 Crew

NASA Image and Video Library

2007-09-01

ISS015-E-26171 (1 Sept. 2007) --- Simushir Island, Kuril Archipelago, Russian Far East, is featured in this image photographed by an Expedition 15 crewmember on the International Space Station. Simushir is a deserted, 5-mile-wide volcanic island in the Kuril island chain, half way between northern Japan and the Kamchatka Peninsula of Russia. Four volcanoes - Milne, Prevo, Urataman and Zavaritski - have built cones that are high enough to rise above the altitude of green forest. The remaining remnant of Zavaritski volcano is a caldera -- a structure formed when a volcano collapses into its emptied magma chamber. A small lake fills the innermost of three nested calderas which make up Zavaritski Caldera. The larger caldera of Urataman Volcano is connected to the sea. A defunct Soviet naval base occupies the northern tip of the island next to this caldera. The islands and volcanoes of the Kuril chain are part of the Pacific Rim of Fire, marking the edge of the Pacific tectonic plate. Low stratus clouds approaching from the northwest (from the Sea of Okhotsk--top left) bank up against the northwest side of the island, making complex cloud patterns. A small finger of cloud can be seen entering the northernmost caldera (Urataman) at sea level. When this image was taken, the cloud layer had stopped at the northwest coast of the island, not flowing over even the low points of the island between the volcanoes. The cloud pattern suggests that the air mass flowed up and over the island, descending on the southeast side. This descending motion was enough--under stable atmospheric conditions--to warm up the atmosphere locally so that a cloud-free zone formed on the southeastern, lee side of the island.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.

PubMed

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-12-16

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.

Evaluation of a rule-based compositing technique for Landsat-5 TM and Landsat-7 ETM+ images

NASA Astrophysics Data System (ADS)

Lück, W.; van Niekerk, A.

2016-05-01

Image compositing is a multi-objective optimization process. Its goal is to produce a seamless cloud and artefact-free artificial image. This is achieved by aggregating image observations and by replacing poor and cloudy data with good observations from imagery acquired within the timeframe of interest. This compositing process aims to minimise the visual artefacts which could result from different radiometric properties, caused by atmospheric conditions, phenologic patterns and land cover changes. It has the following requirements: (1) image compositing must be cloud free, which requires the detection of clouds and shadows, and (2) the image composite must be seamless, minimizing artefacts and visible across inter image seams. This study proposes a new rule-based compositing technique (RBC) that combines the strengths of several existing methods. A quantitative and qualitative evaluation is made of the RBC technique by comparing it to the maximum NDVI (MaxNDVI), minimum red (MinRed) and maximum ratio (MaxRatio) compositing techniques. A total of 174 Landsat TM and ETM+ images, covering three study sites and three different timeframes for each site, are used in the evaluation. A new set of quantitative/qualitative evaluation techniques for compositing quality measurement was developed and showed that the RBC technique outperformed all other techniques, with MaxRatio, MaxNDVI, and MinRed techniques in order of performance from best to worst.

Extratropical Cyclone in the Southern Ocean

NASA Technical Reports Server (NTRS)

2001-01-01

These images from the Multi-angle Imaging SpectroRadiometer portray an occluded extratropical cyclone situated in the Southern Ocean, about 650 kilometers south of the Eyre Peninsula, South Australia.

Parts of the Yorke Peninsula and a portion of the Murray-Darling River basin are visible between the clouds near the top of the left-hand image, a true-color view from MISR's nadir(vertical-viewing) camera. Retrieved cloud-tracked wind velocities are indicated by the superimposed arrows. The image on the right displays cloud-top heights. Areas where cloud heights could not be retrieved are shown in black. Both the wind vectors and the cloud heights were derived using data from multiple MISR cameras within automated computer processing algorithms. The stereoscopic algorithms used to generate these results are still being refined, and future versions of these products may show modest changes.

Extratropical cyclones are the dominant weather system at midlatitudes, and the term is used generically for region allow-pressure systems in the mid- to high-latitudes. In the southern hemisphere, cyclonic rotation is clockwise. These storms obtain their energy from temperature differences between air masses on either side of warm and cold fronts, and their characteristic pattern is of warm and cold fronts radiating out from a migrating low pressure center which forms, deepens, and dissipates as the fronts fold and collapse on each other. The center of this cyclone has started to decay, with the band of cloud to the south most likely representing the main front that was originally connected with the cyclonic circulation.

These views were acquired on October 11, 2001 during Terra orbit 9650, and represent an area of about 380 kilometers x 1900 kilometers.

Jupiter's Equatorial Region in the Two Methane Bands (Time set 2)

NASA Technical Reports Server (NTRS)

1997-01-01

Mosaics of an equatorial 'hotspot' on Jupiter at 727 nanometers (top) and 889 nanometers (bottom). The mosaics cover an area of 34,000 kilometers by 11,000 kilometers. The darker region near the center of each mosaic is an equatorial 'hotspot' similar to the Galileo Probe entry site. These features are holes in the bright, reflective, equatorial cloud layer where warmer thermal emission from Jupiter's deep atmosphere can pass through. The circulation patterns observed here along with the composition measurements from the Galileo Probe suggest that dry air may be converging and sinking over these regions, maintaining their cloud-free appearance.

Light at 727 nanometers (nm) is moderately absorbed by atmospheric methane. This mosaic shows the features of Jupiter's main visible cloud deck and upper tropospheric haze, with higher features enhanced in brightness over lower features. Light at 889 nm is strongly absorbed by atmospheric methane. This mosaic shows the features of a hazy cloud layer tens of kilometers above Jupiter's main visible cloud deck. This haze varies in height but appears to be present over the entire region. Small patches of very bright clouds may be similar to terrestrial thunderstorms. Together images at these wavelengths provide a three dimensional view of the cloud layers in Jupiter's atmosphere.

North is at the top. The mosaics cover latitudes 1 to 10 degrees and are centered at longitude 336 degrees West. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers by the Solid State Imaging system aboard NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Three dimensional Visualization of Jupiter's Equatorial Region

NASA Technical Reports Server (NTRS)

1997-01-01

Frames from a three dimensional visualization of Jupiter's equatorial region. The images used cover an area of 34,000 kilometers by 11,000 kilometers (about 21,100 by 6,800 miles) near an equatorial 'hotspot' similar to the site where the probe from NASA's Galileo spacecraft entered Jupiter's atmosphere on December 7th, 1995. These features are holes in the bright, reflective, equatorial cloud layer where warmer thermal emission from Jupiter's deep atmosphere can pass through. The circulation patterns observed here along with the composition measurements from the Galileo Probe suggest that dry air may be converging and sinking over these regions, maintaining their cloud-free appearance. The bright clouds to the right of the hotspot as well as the other bright features may be examples of upwelling of moist air and condensation.

This frame is a view from above and to the south of the visualized area, showing the entire model. The entire region is overlain by a thin, transparent haze. In places the haze is high and thick, especially to the east (to the right of) the hotspot.

Galileo is the first spacecraft to image Jupiter in near-infrared light (which is invisible to the human eye) using three filters at 727, 756, and 889 nanometers (nm). Because light at these three wavelengths is absorbed at different altitudes by atmospheric methane, a comparison of the resulting images reveals information about the heights of clouds in Jupiter's atmosphere. This information can be visualized by rendering cloud surfaces with the appropriate height variations.

The visualization reduces Jupiter's true cloud structure to two layers. The height of a high haze layer is assumed to be proportional to the reflectivity of Jupiter at 889 nm. The height of a lower tropospheric cloud is assumed to be proportional to the reflectivity at 727 nm divided by that at 756 nm. This model is overly simplistic, but is based on more sophisticated studies of Jupiter's cloud structure. The upper and lower clouds are separated in the rendering by an arbitrary amount, and the height variations are exaggerated by a factor of 25.

The lower cloud is colored using the same false color scheme used in previously released image products, assigning red, green, and blue to the 756, 727, and 889 nanometer mosaics, respectively. Light bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the lower cloud with an overlying thin haze.

The images used cover latitudes 1 to 10 degrees and are centered at longitude 336 degrees west. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers (about 930,000 miles) by the Solid State Imaging (CCD) system on NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the Galileo mission for NASA's Office of Space Science, Washington, DC. JPL is an operating division of California Institute of Technology (Caltech).

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://www.jpl.nasa.gov/ galileo.

Deep Learning for Discovery of Atmospheric Mountain Waves in MODIS and GPS Data

NASA Astrophysics Data System (ADS)

Pankratius, V.; Li, J. D.; Rude, C. M.; Gowanlock, M.; Herring, T.

2017-12-01

Airflow over mountains can produce gravity waves, called lee waves, which can generate atmospheric turbulence. Since this turbulence poses dangers to aviation, it is critical to identify such regions reliably in an automated fashion. This work leverages two sources of data to go beyond an ad-hoc human visual approach for such identification: MODIS imagery containing cloud patterns formed by lee waves, and patterns in GPS signals resulting from the transmission through atmospheric turbulence due to lee waves. We demonstrate a novel machine learning approach that fuses these two data types to detect atmospheric turbulence associated with lee waves. A convolutional neural network is trained on MODIS tile images to automatically classify the lee wave cloud patterns with 96% correct classifications on a validation set of 20,000 MODIS 64x64 tiles over a test region in the Sierra Nevada Mountains. Signals from GPS stations of the Plate Boundary Observatory are used for feature extraction related to lee waves, in order to improve the confidence of a detection in the MODIS imagery at a given position. To our knowledge, this is the first technique to combine these images and time series data types to improve the spatial and temporal resolutions for large-scale measurements of lee wave formations. First results of this work show great potential for improving weather condition monitoring, hazard and cloud pattern detection, as well as GPS navigation uncertainties. We acknowledge support from NASA AISTNNX15AG84G (PI Pankratius), NASA NNX14AQ03G (PI Herring), and NSF ACI1442997 (PI Pankratius).

Earth Observations taken by Expedition 38 crewmember

NASA Image and Video Library

2014-01-28

ISS038-E-036501 (28 Jan. 2014) --- This wide field-of-view image photographed by an Expedition 38 crew member on the International Space Station shows an east-west swath of the southwestern Indian Ocean. Two remote islands, part of the French Southern and Antarctic Lands, appear in the center of the image. Possession Island (right center) and East Island (center) are both only 18 kilometers long. A smaller island, Ile aux Cochons (Pigs Island), lies 100 kilometers to the west. Each island has set up V-shaped trains of waves, like bow waves, as the air flows over the islands from the west (right to left). The bow-wave patterns are overlaid on the low regional stratus (blanket) cloud that is so common in the southern Indian Ocean at 50 degrees south latitude. This view was taken from more than 400 kilometers above the sea surface and reveals relationships that could not be readily understood by someone standing on one of the islands. For example, larger and higher islands produce larger waves. So the largest are being generated by Possession Island (934 meters above sea level at the highest point), and East Island, versus much smaller waves developed downwind of the tiny Ile de Pingouins (340 meters above sea level high, invisible below the cloud deck). Other patterns also can be detected. Waves in an upper layer can be seen casting shadows onto a lower layer (lower left). In the top half of the image the waves are making thicker and thinner zones in the clouds of the lower layer. Wave trains from Possession Island and Ile aux Cochons are interacting in a cross-hatch pattern (center).

Mesopause Horizontal wind estimates based on AIM CIPS polar mesospheric cloud pattern matching

NASA Astrophysics Data System (ADS)

Rong, P.; Yue, J.; Russell, J. M.; Gong, J.; Wu, D. L.; Randall, C. E.

2013-12-01

A cloud pattern matching approach is used to estimate horizontal winds in the mesopause region using Polar Mesospheric Cloud (PMC) albedo data measured by the Cloud Imaging and Particle Size instrument on the AIM satellite. Measurements for all 15 orbits per day throughout July 2007 are used to achieve statistical significance. For each orbit, eighteen out of the twenty-seven scenes are used for the pattern matching operation. Some scenes at the lower latitudes are not included because there is barely any cloud coverage for these scenes. The frame-size chosen is about 12 degrees in longitude and 3 degrees in latitude. There is no strict criterion in choosing the frame size since PMCs are widespread in the polar region and most local patterns do not have a clearly defined boundary. The frame moves at a step of 1/6th of the frame size in both the longitudinal and latitudinal directions to achieve as many 'snap-shots' as possible. A 70% correlation is used as a criterion to define an acceptable match between two patterns at two time frames; in this case the time difference is about 3.6 minutes that spans every 5 'bowtie' scenes. A 70% criterion appears weak if the chosen pattern is expected to act like a tracer. It is known that PMC brightness varies rapidly with a changing temperature and water vapor environment or changing nucleation conditions, especially on smaller spatial scales; therefore PMC patterns are not ideal tracers. Nevertheless, within a short time span such as 3.6 minutes a 70% correlation is sufficient to identify two cloud patterns that come from the same source region, although the two patterns may exhibit a significant difference in the actual brightness. Analysis of a large number of matched cloud patterns indicates that over the 3.6-minute time span about 70% of the patterns remain in the same locations. Given the 25-km2 horizontal resolution of CIPS data, this suggests that the overall magnitude of horizontal wind at PMC altitudes (~80-87 km) in the polar summer cannot exceed 25 m/s. In other words, the wind detection resolution is no better than 25 m/s. There are about 10% of cases in which it appears that an easterly prevails, with a peak value at about 80-100m/s. In another 5% of cases a westerly appears to prevail. The remaining 15% cases are related to either invalid cloud features with poor background correction or the situation in which the matching occurs at the corners of the bowties. The AIM CIPS cloud pattern matching results overall suggest that higher wind speed (25-200 m/s) can be reached occasionally, while in a majority of cases the wind advection caused albedo change is much smaller than the in-situ albedo change. However, we must note that this analysis was a feasibility study and the short period analyzed may not be representative of the winds over a seasonal time scale or the multiple-year average.

An automated method for tracking clouds in planetary atmospheres

NASA Astrophysics Data System (ADS)

Luz, D.; Berry, D. L.; Roos-Serote, M.

2008-05-01

We present an automated method for cloud tracking which can be applied to planetary images. The method is based on a digital correlator which compares two or more consecutive images and identifies patterns by maximizing correlations between image blocks. This approach bypasses the problem of feature detection. Four variations of the algorithm are tested on real cloud images of Jupiter's white ovals from the Galileo mission, previously analyzed in Vasavada et al. [Vasavada, A.R., Ingersoll, A.P., Banfield, D., Bell, M., Gierasch, P.J., Belton, M.J.S., Orton, G.S., Klaasen, K.P., Dejong, E., Breneman, H.H., Jones, T.J., Kaufman, J.M., Magee, K.P., Senske, D.A. 1998. Galileo imaging of Jupiter's atmosphere: the great red spot, equatorial region, and white ovals. Icarus, 135, 265, doi:10.1006/icar.1998.5984]. Direct correlation, using the sum of squared differences between image radiances as a distance estimator (baseline case), yields displacement vectors very similar to this previous analysis. Combining this distance estimator with the method of order ranks results in a technique which is more robust in the presence of outliers and noise and of better quality. Finally, we introduce a distance metric which, combined with order ranks, provides results of similar quality to the baseline case and is faster. The new approach can be applied to data from a number of space-based imaging instruments with a non-negligible gain in computing time.

Jupiter's Northern Hemisphere in the Near-Infrared (Time Set 3)

NASA Technical Reports Server (NTRS)

1997-01-01

Mosaic of Jupiter's northern hemisphere between 10 and 50 degrees latitude. Jupiter's atmospheric circulation is dominated by alternating eastward and westward jets from equatorial to polar latitudes. The direction and speed of these jets in part determine the color and texture of the clouds seen in this mosaic. Also visible are several other common Jovian cloud features, including large white ovals, bright spots, dark spots, interacting vortices, and turbulent chaotic systems. The north-south dimension of each of the two interacting vortices in the upper half of the mosaic is about 3500 kilometers. The near-infrared continuum filter (756 nanometers) shows the features of Jupiter's main visible cloud deck.

North is at the top. The images are projected on a sphere, with features being foreshortened towards the north. The planetary limb runs along the right edge of the mosaic. Cloud patterns appear foreshortened as they approach the limb. The smallest resolved features are tens of kilometers in size. These images were taken on April 3, 1997, at a range of 1.4 million kilometers by the Solid State Imaging system (CCD) on NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Time-lapse Sequence of Jupiter's South Pole

NASA Image and Video Library

2018-02-22

This series of images captures cloud patterns near Jupiter's south pole, looking up towards the planet's equator. NASA's Juno spacecraft took the color-enhanced time-lapse sequence of images during its eleventh close flyby of the gas giant planet on Feb. 7 between 7:21 a.m. and 8:01 a.m. PST (10:21 a.m. and 11:01 a.m. EST). At the time, the spacecraft was between 85,292 to 124,856 miles (137,264 to 200,937 kilometers) from the tops of the clouds of the planet with the images centered on latitudes from 84.1 to 75.5 degrees south. At first glance, the series might appear to be the same image repeated. But closer inspection reveals slight changes, which are most easily noticed by comparing the far left image with the far right image. Directly, the images show Jupiter. But, through slight variations in the images, they indirectly capture the motion of the Juno spacecraft itself, once again swinging around a giant planet hundreds of millions of miles from Earth. https://photojournal.jpl.nasa.gov/catalog/PIA21979

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation

PubMed Central

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-01-01

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency. PMID:27999261

- and Scene-Guided Integration of Tls and Photogrammetric Point Clouds for Landslide Monitoring

NASA Astrophysics Data System (ADS)

Zieher, T.; Toschi, I.; Remondino, F.; Rutzinger, M.; Kofler, Ch.; Mejia-Aguilar, A.; Schlögel, R.

2018-05-01

Terrestrial and airborne 3D imaging sensors are well-suited data acquisition systems for the area-wide monitoring of landslide activity. State-of-the-art surveying techniques, such as terrestrial laser scanning (TLS) and photogrammetry based on unmanned aerial vehicle (UAV) imagery or terrestrial acquisitions have advantages and limitations associated with their individual measurement principles. In this study we present an integration approach for 3D point clouds derived from these techniques, aiming at improving the topographic representation of landslide features while enabling a more accurate assessment of landslide-induced changes. Four expert-based rules involving local morphometric features computed from eigenvectors, elevation and the agreement of the individual point clouds, are used to choose within voxels of selectable size which sensor's data to keep. Based on the integrated point clouds, digital surface models and shaded reliefs are computed. Using an image correlation technique, displacement vectors are finally derived from the multi-temporal shaded reliefs. All results show comparable patterns of landslide movement rates and directions. However, depending on the applied integration rule, differences in spatial coverage and correlation strength emerge.

Study of sea ice in the Sea of Okhotsk and its influence on the Oyashio current

NASA Technical Reports Server (NTRS)

Watanabe, K.; Kuroda, R.; Hata, K.; Akagawa, M. (Principal Investigator)

1975-01-01

The author has identified the following significant results. Two photographic techniques were applied to Skylab S190A multispectral pictures for extracting oceanic patterns at the sea surface separately from cloud patterns. One is the image-masking technique and another a stereographic analysis. The extracted oceanic patterns were interpreted as areas where the amount, or the concentration of phytoplankton was high by utilizing surface data of water temperature, ocean current by GEK, and microplankton.

Thin Cloud Detection Method by Linear Combination Model of Cloud Image

NASA Astrophysics Data System (ADS)

Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.

2018-04-01

The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed cloud detection program in this paper has high accuracy and fast calculation speed.

Prediction of optical communication link availability: real-time observation of cloud patterns using a ground-based thermal infrared camera

NASA Astrophysics Data System (ADS)

Bertin, Clément; Cros, Sylvain; Saint-Antonin, Laurent; Schmutz, Nicolas

2015-10-01

The growing demand for high-speed broadband communications with low orbital or geostationary satellites is a major challenge. Using an optical link at 1.55 μm is an advantageous solution which potentially can increase the satellite throughput by a factor 10. Nevertheless, cloud cover is an obstacle for this optical frequency. Such communication requires an innovative management system to optimize the optical link availability between a satellite and several Optical Ground Stations (OGS). The Saint-Exupery Technological Research Institute (France) leads the project ALBS (French acronym for BroadBand Satellite Access). This initiative involving small and medium enterprises, industrial groups and research institutions specialized in aeronautics and space industries, is currently developing various solutions to increase the telecommunication satellite bandwidth. This paper presents the development of a preliminary prediction system preventing the cloud blockage of an optical link between a satellite and a given OGS. An infrared thermal camera continuously observes (night and day) the sky vault. Cloud patterns are observed and classified several times a minute. The impact of the detected clouds on the optical beam (obstruction or not) is determined by the retrieval of the cloud optical depth at the wavelength of communication. This retrieval is based on realistic cloud-modelling on libRadtran. Then, using subsequent images, cloud speed and trajectory are estimated. Cloud blockage over an OGS can then be forecast up to 30 minutes ahead. With this information, the preparation of the new link between the satellite and another OGS under a clear sky can be prepared before the link breaks due to cloud blockage.

Monthly and Seasonal Cloud Cover Patterns at the Manila Observatory (14.64°N, 121.08°E)

NASA Astrophysics Data System (ADS)

Antioquia, C. T.; Lagrosas, N.; Caballa, K.

2014-12-01

A ground based sky imaging system was developed at the Manila Observatory in 2012 to measure cloud occurrence and to analyse seasonal variation of cloud cover over Metro Manila. Ground-based cloud occurrence measurements provide more reliable results compared to satellite observations. Also, cloud occurrence data aid in the analysis of radiation budget in the atmosphere. In this study, a GoPro Hero 2 with almost 180o field of view is employed to take pictures of the atmosphere. These pictures are taken continuously, having a temporal resolution of 1min. Atmospheric images from April 2012 to June 2013 (excluding the months of September, October, and November 2012) were processed to determine cloud cover. Cloud cover in an image is measured as the ratio of the number of pixels with clouds present in them to the total number of pixels. The cloud cover values were then averaged over each month to know its monthly and seasonal variation. In Metro Manila, the dry season occurs in the months of November to May of the next year, while the wet season occurs in the months of June to October of the same year. Fig 1 shows the measured monthly variation of cloud cover. No data was collected during the months of September (wherein the camera was used for the 7SEAS field campaign), October, and November 2012 (due to maintenance and repairs). Results show that there is high cloud cover during the wet season months (80% on average) while there is low cloud cover during the dry season months (62% on average). The lowest average cloud cover for a wet season month occurred in June 2012 (73%) while the highest average cloud cover for a wet season month occurred in June 2013 (86%). The variations in cloud cover average in this season is relatively smaller compared to that of the dry season wherein the lowest average cloud cover in a month was during April 2012 (38%) while the highest average cloud cover in a month was during January 2013 (77%); minimum and maximum averages being 39% apart. During the wet season, the cloud occurrence is mainly due to tropical storms, Southwest Monsoon, and local convection processes. In the dry season, less cloud is formed because of cold dry air from Northeast Monsoon (December to February) and generally dry and hot weather (March to May). Regular data collection has been implemented for further long term data analysis.

Cloud Imagers Offer New Details on Earth's Health

NASA Technical Reports Server (NTRS)

2009-01-01

A stunning red sunset or purple sunrise is an aesthetic treat with a scientific explanation: The colors are a direct result of the absorption or reflectance of solar radiation by atmospheric aerosols, minute particles (either solid or liquid) in the Earth s atmosphere that occur both naturally and because of human activity. At the beginning or end of the day, the Sun s rays travel farther through the atmosphere to reach an observer s eyes and more green and yellow light is scattered, making the Sun appear red. Sunset and sunrise are especially colorful when the concentration of atmospheric particles is high. This ability of aerosols to absorb and reflect sunlight is not just pretty; it also determines the amount of radiation and heat that reaches the Earth s surface, and can profoundly affect climate. In the atmosphere, aerosols are also important as nuclei for the condensation of water droplets and ice crystals. Clouds with fewer aerosols cannot form as many water droplets (called cloud particles), and consequently, do not scatter light well. In this case, more sunlight reaches the Earth s surface. When aerosol levels in clouds are high, however, more nucleation points can form small liquid water droplets. These smaller cloud particles can reflect up to 90 percent of visible radiation to space, keeping the heat from ever reaching Earth s surface. The tendency for these particles to absorb or reflect the Sun s energy - called extinction by astronomers - depends on a number of factors, including chemical composition and the humidity and temperature in the surrounding air; because cloud particles are so small, they are affected quickly by minute changes in the atmosphere. Because of this sensitivity, atmospheric scientists study cloud particles to anticipate patterns and shifts in climate. Until recently, NASA s study of atmospheric aerosols and cloud particles has been focused primarily on satellite images, which, while granting large-scale atmospheric analysis, limited scientists ability to acquire detailed information about individual particles. Now, experiments with specialized equipment can be flown on standard jets, making it possible for researchers to monitor and more accurately anticipate changes in Earth s atmosphere and weather patterns.

An efficient framework for modeling clouds from Landsat8 images

NASA Astrophysics Data System (ADS)

Yuan, Chunqiang; Guo, Jing

2015-03-01

Cloud plays an important role in creating realistic outdoor scenes for video game and flight simulation applications. Classic methods have been proposed for cumulus cloud modeling. However, these methods are not flexible for modeling large cloud scenes with hundreds of clouds in that the user must repeatedly model each cloud and adjust its various properties. This paper presents a meteorologically based method to reconstruct cumulus clouds from high resolution Landsat8 satellite images. From these input satellite images, the clouds are first segmented from the background. Then, the cloud top surface is estimated from the temperature of the infrared image. After that, under a mild assumption of flat base for cumulus cloud, the base height of each cloud is computed by averaging the top height for pixels on the cloud edge. Then, the extinction is generated from the visible image. Finally, we enrich the initial shapes of clouds using a fractal method and represent the recovered clouds as a particle system. The experimental results demonstrate our method can yield realistic cloud scenes resembling those in the satellite images.

CloudSat Image of Tropical Thunderstorms Over Africa

NASA Technical Reports Server (NTRS)

2006-01-01

[figure removed for brevity, see original site] Figure 1

CloudSat image of a horizontal cross-section of tropical clouds and thunderstorms over east Africa. The red colors are indicative of highly reflective particles such as water (rain) or ice crystals, which the blue indicates thinner clouds (such as cirrus). The flat green/blue lines across the bottom represent the ground signal. The vertical scale on the CloudS at Cloud Profiling Radar image is approximately 30 kilometers (19 miles). The brown line below the image indicates the relative elevation of the land surface. The inset image shows the CloudSat track relative to a Moderate Resolution Imaging Spectroradiometer (MODIS) visible image taken at nearly the same time.

Single shot laser speckle based 3D acquisition system for medical applications

NASA Astrophysics Data System (ADS)

Khan, Danish; Shirazi, Muhammad Ayaz; Kim, Min Young

2018-06-01

The state of the art techniques used by medical practitioners to extract the three-dimensional (3D) geometry of different body parts requires a series of images/frames such as laser line profiling or structured light scanning. Movement of the patients during scanning process often leads to inaccurate measurements due to sequential image acquisition. Single shot structured techniques are robust to motion but the prevalent challenges in single shot structured light methods are the low density and algorithm complexity. In this research, a single shot 3D measurement system is presented that extracts the 3D point cloud of human skin by projecting a laser speckle pattern using a single pair of images captured by two synchronized cameras. In contrast to conventional laser speckle 3D measurement systems that realize stereo correspondence by digital correlation of projected speckle patterns, the proposed system employs KLT tracking method to locate the corresponding points. The 3D point cloud contains no outliers and sufficient quality of 3D reconstruction is achieved. The 3D shape acquisition of human body parts validates the potential application of the proposed system in the medical industry.

Jupiter's Great Red Spot in Cassini image

NASA Technical Reports Server (NTRS)

2000-01-01

This true color image of Jupiter, taken by NASA's Cassini spacecraft, is composed of three images taken in the blue, green and red regions of the spectrum. All images were taken from a distance of 77.6 million kilometers (48.2 million miles) on Oct. 8, 2000.

Different chemical compositions of the cloud particles lead to different colors. The cloud patterns reflect different physical conditions -- updrafts and downdrafts -- in which the clouds form. The bluish areas are believed to be regions devoid of clouds and covered by high haze.

The Great Red Spot (below and to the right of center) is a giant atmospheric storm as wide as two Earths and over 300 years old, with peripheral winds of 483 kilometers per hour (300 miles per hour). This image shows that it is trailed to the north by a turbulent region, caused by atmospheric flow around the spot.

The bright white spots in this region are lightning storms, which were seen by NASA's Galileo spacecraft when it photographed the night side of Jupiter. Cassini will track these lightning storms and measure their lifetimes and motions when it passes Jupiter in late December and looks back on the darkside of the planet. Cassini is currently en route to its ultimate destination, Saturn.

The resolution is 466 kilometers (290 miles) per picture element.

Cassini is a cooperative project of NASA, the European Space Agency and the Italian Space Agency. The Jet Propulsion Laboratory, a division of the California Institute of Technology in Pasadena, Calif., manages the Cassini mission for NASA's Office of Space Science, Washington, D.C.

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

NASA Technical Reports Server (NTRS)

Wu, D. L.; Kelly, M.A.; Yee, J.-H.; Boldt, J.; Demajistre, R.; Reynolds, E. L.; Tripoli, G. J.; Oman, L. D.; Prive, N.; Heidinger, A. K.;

Pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform

NASA Astrophysics Data System (ADS)

Shi, Cheng; Liu, Fang; Li, Ling-Ling; Hao, Hong-Xia

2014-01-01

The goal of pan-sharpening is to get an image with higher spatial resolution and better spectral information. However, the resolution of the pan-sharpened image is seriously affected by the thin clouds. For a single image, filtering algorithms are widely used to remove clouds. These kinds of methods can remove clouds effectively, but the detail lost in the cloud removal image is also serious. To solve this problem, a pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform (NSST) is proposed. For the low-resolution multispectral (LR MS) and high-resolution panchromatic images with thin clouds, a mask dodging method is used to remove clouds. For the cloud removal LR MS image, an adaptive principal component analysis transform is proposed to balance the spectral information and spatial resolution in the pan-sharpened image. Since the clouds removal process causes the detail loss problem, a weight matrix is designed to enhance the details of the cloud regions in the pan-sharpening process, but noncloud regions remain unchanged. And the details of the image are obtained by NSST. Experimental results over visible and evaluation metrics demonstrate that the proposed method can keep better spectral information and spatial resolution, especially for the images with thin clouds.

An enhanced neighborhood similar pixel interpolator approach for removing thick clouds in landsat images

USDA-ARS?s Scientific Manuscript database

Thick cloud contaminations in Landsat images limit their regular usage for land applications. A few methods have been developed to remove thick clouds using additional cloud-free images. Unfortunately, the cloud-free composition image produced by existing methods commonly lacks from the desired spat...

Jupiter's Southern Exposure in Infrared

NASA Image and Video Library

2018-03-07

This computer-generated image shows the structure of the cyclonic pattern observed over Jupiter's south pole. Like in the North, Jupiter's south pole also contains a central cyclone, but it is surrounded by five cyclones with diameters ranging from 3,500 to 4,300 miles (5,600 to 7,000 kilometers) in diameter. Almost all the polar cyclones (at both poles), are so densely packed that their spiral arms come in contact with adjacent cyclones. However, as tightly spaced as the cyclones are, they have remained distinct, with individual morphologies over the seven months of observations detailed in the paper. The data used in generating this image was collected by the Jovian Infrared Auroral Mapper (JIRAM) instrument aboard the Juno spacecraft during the fourth Juno pass over Jupiter on Feb. 2, 2017. JIRAM is able to collect images in the infrared wavelengths around 5 micrometers (µm) by measuring the intensity of the heat coming out of the planet. The heat from the planet is radiated to space and it is called radiance. This image is an enhancement of the original JIRAM image. In order to give the picture a 3-D shape, the enhancement starts from the idea that the radiance has its highest value where there are no clouds and JIRAM can see deeper into the atmosphere. Consequently, all the other areas of the image are originally shaded more or less by clouds of different thickness. Then, to create these pictures, the originals have been inverted to give the thicker clouds the whitish color and the third dimension that we see with normal clouds here in the Earth's atmosphere. https://photojournal.jpl.nasa.gov/catalog/PIA22337

Jupiter's Northern Hemisphere in a Methane Band (Time Set 3)

NASA Technical Reports Server (NTRS)

1997-01-01

Mosaic of Jupiter's northern hemisphere between 10 and 50 degrees latitude. Jupiter's atmospheric circulation is dominated by alternating eastward and westward jets from equatorial to polar latitudes. The direction and speed of these jets in part determine the color and texture of the clouds seen in this mosaic. Also visible are several other common Jovian cloud features, including large white ovals, bright spots, dark spots, interacting vortices, and turbulent chaotic systems. The north-south dimension of each of the two interacting vortices in the upper half of the mosaic is about 3500 kilometers. Light at 727 nanometers is moderately absorbed by atmospheric methane. This mosaic shows the features of Jupiter's main visible cloud deck and upper-tropospheric haze, with higher features enhanced in brightness over lower features.

North is at the top. The images are projected on a sphere, with features being foreshortened towards the north. The planetary limb runs along the right edge of the mosaic. Cloud patterns appear foreshortened as they approach the limb. The smallest resolved features are tens of kilometers in size. These images were taken on April 3, 1997, at a range of 1.4 million kilometers by the Solid State Imaging system (CCD) on NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Neptune Blue-green Atmosphere

NASA Image and Video Library

2000-02-16

Neptune's blue-green atmosphere is shown in greater detail than ever before by the Voyager 2 spacecraft as it rapidly approaches its encounter with the giant planet. This color image, produced from a distance of about 16 million kilometers, shows several complex and puzzling atmospheric features. The Great Dark Spot (GDS) seen at the center is about 13,000 km by 6,600 km in size -- as large along its longer dimension as the Earth. The bright, wispy "cirrus-type" clouds seen hovering in the vicinity of the GDS are higher in altitude than the dark material of unknown origin which defines its boundaries. A thin veil often fills part of the GDS interior, as seen on the image. The bright cloud at the southern (lower) edge of the GDS measures about 1,000 km in its north-south extent. The small, bright cloud below the GDS, dubbed the "scooter," rotates faster than the GDS, gaining about 30 degrees eastward (toward the right) in longitude every rotation. Bright streaks of cloud at the latitude of the GDS, the small clouds overlying it, and a dimly visible dark protrusion at its western end are examples of dynamic weather patterns on Neptune, which can change significantly on time scales of one rotation (about 18 hours). https://photojournal.jpl.nasa.gov/catalog/PIA02245

Neptune's blue-green atmosphere

NASA Technical Reports Server (NTRS)

1989-01-01

Neptune's blue-green atmosphere is shown in greater detail than ever before by the Voyager 2 spacecraft as it rapidly approaches its encounter with the giant planet. This color image, produced from a distance of about 16 million kilometers, shows several complex and puzzling atmospheric features. The Great Dark Spot (GDS) seen at the center is about 13,000 km by 6,600 km in size -- as large along its longer dimension as the Earth. The bright, wispy 'cirrus-type' clouds seen hovering in the vicinity of the GDS are higher in altitude than the dark material of unknown origin which defines its boundaries. A thin veil often fills part of the GDS interior, as seen on the image. The bright cloud at the southern (lower) edge of the GDS measures about 1,000 km in its north-south extent. The small, bright cloud below the GDS, dubbed the 'scooter,' rotates faster than the GDS, gaining about 30 degrees eastward (toward the right) in longitude every rotation. Bright streaks of cloud at the latitude of the GDS, the small clouds overlying it, and a dimly visible dark protrusion at its western end are examples of dynamic weather patterns on Neptune, which can change significantly on time scales of one rotation (about 18 hours).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoth, Gregory W., E-mail: gregory.hoth@nist.gov; Pelle, Bruno; Riedl, Stefan

We demonstrate a two axis gyroscope by the use of light pulse atom interferometry with an expanding cloud of atoms in the regime where the cloud has expanded by 1.1–5 times its initial size during the interrogation. Rotations are measured by analyzing spatial fringe patterns in the atom population obtained by imaging the final cloud. The fringes arise from a correlation between an atom's initial velocity and its final position. This correlation is naturally created by the expansion of the cloud, but it also depends on the initial atomic distribution. We show that the frequency and contrast of these spatialmore » fringes depend on the details of the initial distribution and develop an analytical model to explain this dependence. We also discuss several challenges that must be overcome to realize a high-performance gyroscope with this technique.« less

ARC-1990-A91-2000

NASA Image and Video Library

1990-02-12

Range : 1 million miles (1.63 million km) This image of the planet Venus was taken by NASA's Galileo spacecraft shortly befor 10pm PST when the space craft was directly above Venus' equator. This is the 66th of more than 80 Venus images Galileo was programmed to take and record during its Venus flyby. In the picture, cloud features as small as 25 miles (40 km) can be seen. Patches of waves and convective clouds are superimpposed on the swirl of the planet's broad weather patterns, marked by the dark chevron at the center. North is at the top. The several ring-shaped shadows are blemishes, not planetary features. The spacecraft imaging system has a 1500-mm, f/8.5 reflecting telescope; the exposure time was 1/40 second. The image was taken through the violet filter (0.41 micron.). It was produced by the imaging system in digital form, as a set of numbers representing the brightness perceived in each of the 640,000 picture elements defined on the solid-state plate, called a charged-coupled-device or CCD, on which the image was focused.

Photogrammetry and photo interpretation applied to analyses of cloud cover, cloud type, and cloud motion

NASA Technical Reports Server (NTRS)

Larsen, P. A.

1972-01-01

A determination was made of the areal extent of terrain obscured by clouds and cloud shadows on a portion of an Apollo 9 photograph at the instant of exposure. This photogrammetrically determined area was then compared to the cloud coverage reported by surface weather observers at approximately the same time and location, as a check on result quality. Stereograms prepared from Apollo 9 vertical photographs, illustrating various percentages of cloud coverage, are presented to help provide a quantitative appreciation of the degradation of terrain photography by clouds and their attendant shadows. A scheme, developed for the U.S. Navy, utilizing pattern recognition techniques for determining cloud motion from sequences of satellite photographs, is summarized. Clouds, turbulence, haze, and solar altitude, four elements of our natural environment which affect aerial photographic missions, are each discussed in terms of their effects on imagery obtained by aerial photography. Data of a type useful to aerial photographic mission planners, expressing photographic ground coverage in terms of flying height above terrain and camera focal length, for a standard aerial photograph format, are provided. Two oblique orbital photographs taken during the Apollo 9 flight are shown, and photo-interpretations, discussing the cloud types imaged and certain visible geographical features, are provided.

Meteorology of Jupiter's Equatorial Hot Spots and Plumes from Cassini

NASA Technical Reports Server (NTRS)

Choi, David Sanghun; Showman, Adam P.; Vasavada, Ashwin R.; Simon-Miller, Amy A.

2013-01-01

We present an updated analysis of Jupiter's equatorial meteorology from Cassini observations. For two months preceding the spacecraft's closest approach, the Imaging Science Subsystem (ISS) onboard regularly imaged the atmosphere. We created time-lapse movies from this period in order to analyze the dynamics of equatorial hot spots and their interactions with adjacent latitudes. Hot spots are relatively cloud-free regions that emit strongly at 5 lm; improved knowledge of these features is crucial for fully understanding Galileo probe measurements taken during its descent through one. Hot spots are quasistable, rectangular dark areas on visible-wavelength images, with defined eastern edges that sharply contrast with surrounding clouds, but diffuse western edges serving as nebulous boundaries with adjacent equatorial plumes. Hot spots exhibit significant variations in size and shape over timescales of days and weeks. Some of these changes correspond with passing vortex systems from adjacent latitudes interacting with hot spots. Strong anticyclonic gyres present to the south and southeast of the dark areas appear to circulate into hot spots. Impressive, bright white plumes occupy spaces in between hot spots. Compact cirrus-like 'scooter' clouds flow rapidly through the plumes before disappearing within the dark areas. These clouds travel at 150-200 m/s, much faster than the 100 m/s hot spot and plume drift speed. This raises the possibility that the scooter clouds may be more illustrative of the actual jet stream speed at these latitudes. Most previously published zonal wind profiles represent the drift speed of the hot spots at their latitude from pattern matching of the entire longitudinal image strip. If a downward branch of an equatorially-trapped Rossby wave controls the overall appearance of hot spots, however, the westward phase velocity of the wave leads to underestimates of the true jet stream speed.

Space Science

NASA Image and Video Library

2001-09-30

Absorption of solar energy heats up our planet's surface and atmosphere making life for us possible. But the energy carnot stay bound up in the Earth's environment forever. If it did, the Earth would be as hot as the sun. Instead, as the surface and atmosphere warm, they emit thermal long wave radiation, some of which escapes into space and allows the Earth to cool. This false color image of the Earth was produced by the Clouds and the Earth's Radiant Energy System (CERES) instrument flying aboard NASA's Terra spacecraft. The image shows where more or less heat, in the form of long-wave radiation, is emanating from the top of the Earth's atmosphere. As one can see in the image, the thermal radiation leaving the oceans is fairly uniform. The blue swaths represent thick clouds, the tops of which are so high they are among the coldest places on Earth. In the American Southwest, which can be seen in the upper right hand corner of the globe, there is often little cloud cover to block outgoing radiation and relatively little water to absorb solar energy making the amount of outgoing radiation in this area exceeding that of the oceans. Recently, NASA researchers discovered that incoming solar radiation and outgoing thermal radiation increased in the tropics from the 1980s to the 1990s. They believe the unexpected change has to do with apparent change in circulation patterns around the globe, which effectively reduce the amount of water vapor and cloud cover in the upper reaches of the atmosphere. Without the clouds, more sunlight was allowed to enter the tropical zones and more thermal energy was allowed to leave. The findings may have big implications for climate change and future global warming. (Image courtesy NASA Goddard)

a Novel Ship Detection Method for Large-Scale Optical Satellite Images Based on Visual Lbp Feature and Visual Attention Model

NASA Astrophysics Data System (ADS)

Haigang, Sui; Zhina, Song

2016-06-01

Reliably ship detection in optical satellite images has a wide application in both military and civil fields. However, this problem is very difficult in complex backgrounds, such as waves, clouds, and small islands. Aiming at these issues, this paper explores an automatic and robust model for ship detection in large-scale optical satellite images, which relies on detecting statistical signatures of ship targets, in terms of biologically-inspired visual features. This model first selects salient candidate regions across large-scale images by using a mechanism based on biologically-inspired visual features, combined with visual attention model with local binary pattern (CVLBP). Different from traditional studies, the proposed algorithm is high-speed and helpful to focus on the suspected ship areas avoiding the separation step of land and sea. Largearea images are cut into small image chips and analyzed in two complementary ways: Sparse saliency using visual attention model and detail signatures using LBP features, thus accordant with sparseness of ship distribution on images. Then these features are employed to classify each chip as containing ship targets or not, using a support vector machine (SVM). After getting the suspicious areas, there are still some false alarms such as microwaves and small ribbon clouds, thus simple shape and texture analysis are adopted to distinguish between ships and nonships in suspicious areas. Experimental results show the proposed method is insensitive to waves, clouds, illumination and ship size.

Severe Storm in the Sea of Azov

NASA Technical Reports Server (NTRS)

2007-01-01

A fierce storm struck both the Black Sea and the Sea of Azov on November 11, 2007. According to news reports, as many as 10 ships either sank or ran aground, one of them an oil tanker. The Russian tanker Volganeft-139 was anchored to the sea floor in the Kerch Strait linking the Black and Azov Seas when 108-kilometer- (67-mile-) per-hour winds tore the ship apart. As of November 12, up to 2,000 metric tons of fuel oil had leaked from the ship. On November 11, 2007, the day the storm struck, the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Aqua satellite captured this image of the region. Thick clouds obscure the view of much of the land area, including Ukraine, Belarus, western Russia, and Georgia. Clouds also obscure the Sea of Azov, although skies over the Black Sea are somewhat clearer. Over the Sea of Azov and immediately to the north, the clouds form a vague swirling pattern, suggestive of a low-pressure cyclonic system.

CloudSat Image of a Polar Night Storm Near Antarctica

NASA Technical Reports Server (NTRS)

2006-01-01

[figure removed for brevity, see original site] Figure 1

CloudSat image of a horizontal cross-section of a polar night storm near Antarctica. Until now, clouds have been hard to observe in polar regions using remote sensing, particularly during the polar winter or night season. The red colors are indicative of highly reflective particles such as water (rain) or ice crystals, while the blue indicates thinner clouds (such as cirrus). The flat green/blue lines across the bottom represent the ground signal. The vertical scale on the CloudSat Cloud Profiling Radar image is approximately 30 kilometers (19 miles). The blue line below the Cloud Profiling Radar image indicates that the data were taken over water; the brown line below the image indicates the relative elevation of the land surface. The inset image shows the CloudSat track relative to a Moderate Resolution Imaging Spectroradiometer (MODIS) infrared image taken at nearly the same time.

Casting Light and Shadows on a Saharan Dust Storm

NASA Technical Reports Server (NTRS)

2003-01-01

On March 2, 2003, near-surface winds carried a large amount of Saharan dust aloft and transported the material westward over the Atlantic Ocean. These observations from the Multi-angle Imaging SpectroRadiometer (MISR) aboard NASA's Terra satellite depict an area near the Cape Verde Islands (situated about 700 kilometers off of Africa's western coast) and provide images of the dust plume along with measurements of its height and motion. Tracking the three-dimensional extent and motion of air masses containing dust or other types of aerosols provides data that can be used to verify and improve computer simulations of particulate transport over large distances, with application to enhancing our understanding of the effects of such particles on meteorology, ocean biological productivity, and human health.

MISR images the Earth by measuring the spatial patterns of reflected sunlight. In the upper panel of the still image pair, the observations are displayed as a natural-color snapshot from MISR's vertical-viewing (nadir) camera. High-altitude cirrus clouds cast shadows on the underlying ocean and dust layer, which are visible in shades of blue and tan, respectively. In the lower panel, heights derived from automated stereoscopic processing of MISR's multi-angle imagery show the cirrus clouds (yellow areas) to be situated about 12 kilometers above sea level. The distinctive spatial patterns of these clouds provide the necessary contrast to enable automated feature matching between images acquired at different view angles. For most of the dust layer, which is spatially much more homogeneous, the stereoscopic approach was unable to retrieve elevation data. However, the edges of shadows cast by the cirrus clouds onto the dust (indicated by blue and cyan pixels) provide sufficient spatial contrast for a retrieval of the dust layer's height, and indicate that the top of layer is only about 2.5 kilometers above sea level.

Motion of the dust and clouds is directly observable with the assistance of the multi-angle 'fly-over' animation (Below). The frames of the animation consist of data acquired by the 70-degree, 60-degree, 46-degree and 26-degree forward-viewing cameras in sequence, followed by the images from the nadir camera and each of the four backward-viewing cameras, ending with 70-degree backward image. Much of the south-to-north shift in the position of the clouds is due to geometric parallax between the nine view angles (rather than true motion), whereas the west-to-east motion is due to actual motion of the clouds over the seven minutes during which all nine cameras observed the scene. MISR's automated data processing retrieved a primarily westerly (eastward) motion of these clouds with speeds of 30-40 meters per second. Note that there is much less geometric parallax for the cloud shadows owing to the relatively low altitude of the dust layer upon which the shadows are cast (the amount of parallax is proportional to elevation and a feature at the surface would have no geometric parallax at all); however, the westerly motion of the shadows matches the actual motion of the clouds. The automated processing was not able to resolve a velocity for the dust plume, but by manually tracking dust features within the plume images that comprise the animation sequence we can derive an easterly (westward) speed of about 16 meters per second. These analyses and visualizations of the MISR data demonstrate that not only are the cirrus clouds and dust separated significantly in elevation, but they exist in completely different wind regimes, with the clouds moving toward the east and the dust moving toward the west.

[figure removed for brevity, see original site]

(Click on image above for high resolution version)

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 17040. The panels cover an area of about 312 kilometers x 242 kilometers, and use data from blocks 74 to 77 within World Reference System-2 path 207.

MISR was built and is managed by NASA's Jet Propulsion Laboratory,Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Antarctic Temperature Extremes from MODIS Land Surface Temperatures: New Processing Methods Reveal Data Quality Puzzles

NASA Astrophysics Data System (ADS)

Grant, G.; Gallaher, D. W.

2017-12-01

New methods for processing massive remotely sensed datasets are used to evaluate Antarctic land surface temperature (LST) extremes. Data from the MODIS/Terra sensor (Collection 6) provides a twice-daily look at Antarctic LSTs over a 17 year period, at a higher spatiotemporal resolution than past studies. Using a data condensation process that creates databases of anomalous values, our processes create statistical images of Antarctic LSTs. In general, the results find few significant trends in extremes; however, they do reveal a puzzling picture of inconsistent cloud detection and possible systemic errors, perhaps due to viewing geometry. Cloud discrimination shows a distinct jump in clear-sky detections starting in 2011, and LSTs around the South Pole exhibit a circular cooling pattern, which may also be related to cloud contamination. Possible root causes are discussed. Ongoing investigations seek to determine whether the results are a natural phenomenon or, as seems likely, the results of sensor degradation or processing artefacts. If the unusual LST patterns or cloud detection discontinuities are natural, they point to new, interesting processes on the Antarctic continent. If the data artefacts are artificial, MODIS LST users should be alerted to the potential issues.

Perspective view, Landsat overlay Oahu, Hawaii

NASA Technical Reports Server (NTRS)

2000-01-01

Honolulu, on the island of Oahu, is a large and growing urban area with limited space and water resources. This perspective view, combining a Landsat image with SRTM topography, shows how the topography controls the urban growth pattern, causes cloud formation, and directs the rainfall runoff pattern. Features of interest in this scene include downtown Honolulu (right), Honolulu Harbor (right), Pearl Harbor (center), and offshore reef patterns (foreground). The Koolau mountain range runs through the center of the image. On the north shore of the island are the Mokapu Peninsula and Kaneohe Bay (upper right). Clouds commonly hang above ridges and peaks of the Hawaiian Islands, and in this rendition appear draped directly on the mountains. The clouds are actually about 1000 meters (3300 feet) above sea level. High resolution topographic and image data allow ecologists and planners to assess the effects of urban development on the sensitive ecosystems in tropical regions.

This type of display adds the important dimension of elevation to the study of land use and environmental processes as observed in satellite images. The perspective view was created by draping a Landsat 7 satellite image over an SRTM elevation model. Topography is exaggerated about six times vertically. The Landsat 7 image was acquired on February 12, 2000, and was provided by the United States Geological Survey's Earth Resources Observations Systems (EROS)Data Center, Sioux Falls, South Dakota.

The Shuttle Radar Topography Mission (SRTM), launched on February 11, 2000, uses the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. The mission is designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, an additional C-band imaging antenna and improved tracking and navigation devices. The mission is a cooperative project between the National Aeronautics and Space Administration (NASA), the National Imagery and Mapping Agency (NIMA) and the German (DLR) and Italian (ASI) space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Earth Science Enterprise, Washington, DC.

Size: 28 by 56 kilometers (17 by 35 miles) Location: 21.4 deg. North lat., 157.8 deg. West lon. Orientation: Looking North Original Data Resolution: SRTM, 30 meters (99 feet); Landsat, 15 meters (50 feet) Date Acquired: SRTM, February 18, 2000; Landsat February 12, 2000 Image: NASA/JPL/NIMA

CloudSat First Image of a Warm Front Storm Over the Norwegian Sea

NASA Technical Reports Server (NTRS)

2006-01-01

[figure removed for brevity, see original site] Figure 1

CloudSat's first image, of a warm front storm over the Norwegian Sea, was obtained on May 20, 2006. In this horizontal cross-section of clouds, warm air is seen rising over colder air as the satellite travels from right to left. The red colors are indicative of highly reflective particles such as water droplets (or rain) or larger ice crystals (or snow), while the blue indicates thinner clouds (such as cirrus). The flat green/blue lines across the bottom represent the ground signal. The vertical scale on the CloudSat Cloud Profiling Radar image is approximately 30 kilometers (19 miles). The blue line below the Cloud Profiling Radar image indicates that the data were taken over water. The inset image shows the CloudSat track relative to a Moderate Resolution Imaging Spectroradiometer (MODIS) infrared image taken at nearly the same time.

Evaluation of Vertical Lacunarity Profiles in Forested Areas Using Airborne Laser Scanning Point Clouds

NASA Astrophysics Data System (ADS)

Székely, B.; Kania, A.; Standovár, T.; Heilmeier, H.

2016-06-01

The horizontal variation and vertical layering of the vegetation are important properties of the canopy structure determining the habitat; three-dimensional (3D) distribution of objects (shrub layers, understory vegetation, etc.) is related to the environmental factors (e.g., illumination, visibility). It has been shown that gaps in forests, mosaic-like structures are essential to biodiversity; various methods have been introduced to quantify this property. As the distribution of gaps in the vegetation is a multi-scale phenomenon, in order to capture it in its entirety, scale-independent methods are preferred; one of these is the calculation of lacunarity. We used Airborne Laser Scanning point clouds measured over a forest plantation situated in a former floodplain. The flat topographic relief ensured that the tree growth is independent of the topographic effects. The tree pattern in the plantation crops provided various quasi-regular and irregular patterns, as well as various ages of the stands. The point clouds were voxelized and layers of voxels were considered as images for two-dimensional input. These images calculated for a certain vicinity of reference points were taken as images for the computation of lacunarity curves, providing a stack of lacunarity curves for each reference points. These sets of curves have been compared to reveal spatial changes of this property. As the dynamic range of the lacunarity values is very large, the natural logarithms of the values were considered. Logarithms of lacunarity functions show canopy-related variations, we analysed these variations along transects. The spatial variation can be related to forest properties and ecology-specific aspects.

Time evolution of surface chlorophyll patterns from cross-spectrum analysis of satellite color images

NASA Technical Reports Server (NTRS)

Denman, Kenneth L.; Abbott, Mark R.

1988-01-01

The rate of decorrelation of surface chlorophyll patterns as a function of the time separation between pairs of images was determined from two sequences of CZCS images of the Pacific Ocean area adjacent to Vancouver Island, Canada; cloud-free subareas were selected that were common to several images separated in time by 1-17 days. Image pairs were subjected to two-dimensional autospectrum and cross-spectrum analysis in an array processor, and squared coherence estimates found for several wave bands were plotted against time separation, in analogy with a time-lagged cross correlation function. It was found that, for wavelengths of 50-150 km, significant coherence was lost after 7-10 days, while for wavelengths of 25-50 km, significant coherence was lost after only 5-7 days. In both cases, offshore regions maintained coherence longer than coastal regions.

Kriging in the Shadows: Geostatistical Interpolation for Remote Sensing

NASA Technical Reports Server (NTRS)

Rossi, Richard E.; Dungan, Jennifer L.; Beck, Louisa R.

1994-01-01

It is often useful to estimate obscured or missing remotely sensed data. Traditional interpolation methods, such as nearest-neighbor or bilinear resampling, do not take full advantage of the spatial information in the image. An alternative method, a geostatistical technique known as indicator kriging, is described and demonstrated using a Landsat Thematic Mapper image in southern Chiapas, Mexico. The image was first classified into pasture and nonpasture land cover. For each pixel that was obscured by cloud or cloud shadow, the probability that it was pasture was assigned by the algorithm. An exponential omnidirectional variogram model was used to characterize the spatial continuity of the image for use in the kriging algorithm. Assuming a cutoff probability level of 50%, the error was shown to be 17% with no obvious spatial bias but with some tendency to categorize nonpasture as pasture (overestimation). While this is a promising result, the method's practical application in other missing data problems for remotely sensed images will depend on the amount and spatial pattern of the unobscured pixels and missing pixels and the success of the spatial continuity model used.

The Radiative Consistency of Atmospheric Infrared Sounder and Moderate Resolution Imaging Spectroradiometer Cloud Retrievals

NASA Technical Reports Server (NTRS)

Kahn, Brian H.; Fishbein, Evan; Nasiri, Shaima L.; Eldering, Annmarie; Fetzer, Eric J.; Garay, Michael J.; Lee, Sung-Yung

2007-01-01

The consistency of cloud top temperature (Tc) and effective cloud fraction (f) retrieved by the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) observation suite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on the EOS-Aqua platform are investigated. Collocated AIRS and MODIS TC and f are compared via an 'effective scene brightness temperature' (Tb,e). Tb,e is calculated with partial field of view (FOV) contributions from TC and surface temperature (TS), weighted by f and 1-f, respectively. AIRS reports up to two cloud layers while MODIS reports up to one. However, MODIS reports TC, TS, and f at a higher spatial resolution than AIRS. As a result, pixel-scale comparisons of TC and f are difficult to interpret, demonstrating the need for alternatives such as Tb,e. AIRS-MODIS Tb,e differences ((Delta)Tb,e) for identical observing scenes are useful as a diagnostic for cloud quantity comparisons. The smallest values of DTb,e are for high and opaque clouds, with increasing scatter in (Delta)Tb,e for clouds of smaller opacity and lower altitude. A persistent positive bias in DTb,e is observed in warmer and low-latitude scenes, characterized by a mixture of MODIS CO2 slicing and 11-mm window retrievals. These scenes contain heterogeneous cloud cover, including mixtures of multilayered cloudiness and misplaced MODIS cloud top pressure. The spatial patterns of (Delta)Tb,e are systematic and do not correlate well with collocated AIRS-MODIS radiance differences, which are more random in nature and smaller in magnitude than (Delta)Tb,e. This suggests that the observed inconsistencies in AIRS and MODIS cloud fields are dominated by retrieval algorithm differences, instead of differences in the observed radiances. The results presented here have implications for the validation of cloudy satellite retrieval algorithms, and use of cloud products in quantitative analyses.

Jupiter's Great Red Spot upper cloud morphology and dynamics from JunoCam images

NASA Astrophysics Data System (ADS)

Sanchez-Lavega, A.; Hueso, R.; Eichstädt, G.; Orton, G.; Rogers, J.; Hansen, C. J.; Momary, T.; Tabataba-Vakili, F.

2017-12-01

We present an analysis of RGB color-composite images of the Great Red Spot (GRS) obtained with JunoCam during Juno's seventh close flyby (PJ7) on July 11, 2017. The images have been projected as 4 cylindrical maps with a resolution of 180 pixels per degree (about 7 km/pixel) spanning a temporal interval of 9 min 41s. The GRS shows a rich variety of cloud morphologies that reveal different dynamical processes in its interior. We consider three major regions. (1) An outer peripheral ring of homogeneous reddish clouds (width about 1,300 km) traces a laminar flow. A family of at least three packets of gravity waves with a mean wavelength of 75 km is present at the internal edge of the ring (in its northern side). They occupy an area of 2,500 km in length (East-West, EW) and 670 km in the North-South (NS) direction. Single clouds in the groups forming the wave have extents of 35 km EW and 70-135 km NS. (2) A large internal region of red clouds (width about 3,200 km) contains three morphologies: (a) fields of bright cumulus-like clusters, (b) long, dark curved filaments (about 7,000 km length with 100 km width), two of them converging into an arrowhead shape, and (c) individual anticyclonic vortices with radius of 500 km that grow due to the radial shear of the wind velocity in the GRS interior as previously measured. A cumulus cluster is conspicuous inside one such anticyclone. Each single cloud element is 50 km in size and the cluster has a 25-30 percent area coverage in cumulus-convective activity, presumably due to ammonia moist convection. (3) A central core has quasi-rectangular shape, extending about 5000 km EW and 3000 km NS, that is confined by elongated clouds distributed along its periphery. Its interior is filled with the redder clouds in the GRS that have a scale 100 km and form a turbulent pattern whose cloud orientations suggest three adjacent areas with alternating cyclonic-cyclonic-anticyclonic vorticity, each with radius 650-850 km.

AIRS First Light Data: Typhoon Ramasun, July 3, 2002

NASA Technical Reports Server (NTRS)

2002-01-01

[figure removed for brevity, see original site] [figure removed for brevity, see original site] Figure 1Figure 2Figure 3

Four images of Tropical Cyclone Ramasun were obtained July 3, 2002 by the Atmospheric Infrared Sounder experiment system onboard NASA's Aqua spacecraft. The AIRS experiment, with its wide spectral coverage in four diverse bands, provides the ability to obtain complete 3-D observations of severe weather, from the surface, through clouds to the top of the atmosphere with unprecedented accuracy. This accuracy is the key to understanding weather patterns and improving weather predictions.

Viewed separately, none of these images can provide accurate 3-D descriptions of the state of the atmosphere because of interference from clouds. However, the ability to make simultaneous observations at a wide range of wavelengths allows the AIRS experiment to 'see' through clouds.

This visible light picture from the AIRS instrument provides important information about the location of the cyclone, cloud structure and distribution.

The AIRS instrument image at 900 cm-1 (Figure 1) is from a 10 micron transparent 'window channel' that is little affected by water vapor but still cannot see through clouds. In clear areas (like the eye of the cyclone and over northwest Australia) it measures a surface temperature of about 300K (color encoded red). In cloudy areas it measures the cloud top temperature, about 200K for the cyclone, which translates to a cloud top height of about 50,000 feet.

On the other hand, most clouds are relatively transparent in microwave, and the Advanced Microwave Sounding Instrument channel image (Figure 2) can see through all but the densest clouds. For example, Taiwan, which is covered by clouds, is clearly visible.

The Humidity Sounder for Brazil instrument channel (Figure 3), also in the microwave, is more sensitive to both clouds and humidity. Only in clear, dry regions, such as the eye of the cyclone or the area north of Australia, does it see the surface. It is also severely affected by suspended ice particles formed by strong convection, which causes scattering and appears to be extremely cold. These blue areas indicate intense precipitation.

The Atmospheric Infrared Sounder is an instrument onboard NASA's Aqua satellite under the space agency's Earth Observing System. The sounding system is making highly accurate measurements of air temperature, humidity, clouds and surface temperature. Data will be used to better understand weather and climate. It will also be used by the National Weather Service and the National Oceanic and Atmospheric Administration to improve the accuracy of their weather and climate models.

The instrument was designed and built by Lockheed Infrared Imaging Systems (recently acquired by British Aerospace) under contract with JPL. The Aqua satellite mission is managed by NASA's Goddard Space Flight Center.

The impact of the use of different satellite data as training data against GOSAT-2 CAI-2 L2 cloud discrimination

NASA Astrophysics Data System (ADS)

Oishi, Y.; Ishida, H.; Nakajima, T. Y.

2016-12-01

Greenhouse gases Observing SATellite-2 (GOSAT-2) will be launched in fiscal 2017 to determine atmospheric concentrations of greenhouse gases, such as CO2, CH4, and CO. GOSAT-2 will be equipped with two sensors: the Thermal and Near-infrared Sensor for Carbon Observation (TANSO)-Fourier Transform Spectrometer-2 (FTS-2) and TANSO-Cloud and Aerosol Imager-2 (CAI-2). CAI-2 is a push-broom imaging sensor that has forward- and backward-looking bands for observing the optical properties of aerosols and clouds, and for monitoring the status of urban air pollution and transboundary air pollution over oceans. An important role of CAI-2 is to perform cloud discrimination in each direction. The Cloud and Aerosol Unbiased Decision Intellectual Algorithm (CLAUDIA1), which applies sequential threshold tests to features, has been used in GOSAT CAI L2 cloud flag processing. If CLAUDIA1 used with CAI-2, it is necessary to optimize the thresholds in accordance with CAI-2. Meanwhile, CLAUDIA3 using support vector machines (SVM), which is a supervised pattern recognition method, was developed for GOSAT-2 CAI-2 L2 cloud discrimination processing. Thus, CLAUDIA3 can automatically find the optimized boundary between clear and cloudy. Improvement of the CLAUDIA3 used with CAI (CLAUDIA3-CAI) has carried out and is still continuing. In this study we compared results of CLAUDIA3-CAI using Terra MODIS data and GOSAT CAI data as training data to clarify the impact of the use of different satellite data as training data against GOSAT-2 CAI-2 L2 cloud discrimination. We will present our latest results.

Cloud Height Estimation with a Single Digital Camera and Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Carretas, Filipe; Janeiro, Fernando M.

2014-05-01

Clouds influence the local weather, the global climate and are an important parameter in the weather prediction models. Clouds are also an essential component of airplane safety when visual flight rules (VFR) are enforced, such as in most small aerodromes where it is not economically viable to install instruments for assisted flying. Therefore it is important to develop low cost and robust systems that can be easily deployed in the field, enabling large scale acquisition of cloud parameters. Recently, the authors developed a low-cost system for the measurement of cloud base height using stereo-vision and digital photography. However, due to the stereo nature of the system, some challenges were presented. In particular, the relative camera orientation requires calibration and the two cameras need to be synchronized so that the photos from both cameras are acquired simultaneously. In this work we present a new system that estimates the cloud height between 1000 and 5000 meters. This prototype is composed by one digital camera controlled by a Raspberry Pi and is installed at Centro de Geofísica de Évora (CGE) in Évora, Portugal. The camera is periodically triggered to acquire images of the overhead sky and the photos are downloaded to the Raspberry Pi which forwards them to a central computer that processes the images and estimates the cloud height in real time. To estimate the cloud height using just one image requires a computer model that is able to learn from previous experiences and execute pattern recognition. The model proposed in this work is an Artificial Neural Network (ANN) that was previously trained with cloud features at different heights. The chosen Artificial Neural Network is a three-layer network, with six parameters in the input layer, 12 neurons in the hidden intermediate layer, and an output layer with only one output. The six input parameters are the average intensity values and the intensity standard deviation of each RGB channel. The output parameter in the output layer is the cloud height estimated by the ANN. The training procedure was performed, using the back-propagation method, in a set of 260 different clouds with heights in the range [1000, 5000] m. The training of the ANN has resulted in a correlation ratio of 0.74. This trained ANN can therefore be used to estimate the cloud height. The previously described system can also measure the wind speed and direction at cloud height by measuring the displacement, in pixels, of a cloud feature between consecutively acquired photos. Also, the geographical north direction can be estimated using this setup through sequential night images with high exposure times. A further advantage of this single camera system is that no camera calibration or synchronization is needed. This significantly reduces the cost and complexity of field deployment of cloud height measurement systems based on digital photography.

Validation of Quasi-Invariant Ice Cloud Radiative Quantities with MODIS Satellite-Based Cloud Property Retrievals

NASA Technical Reports Server (NTRS)

Ding, Jiachen; Yang, Ping; Kattawar, George W.; King, Michael D.; Platnick, Steven; Meyer, Kerry G.

2017-01-01

Similarity relations applied to ice cloud radiance calculations are theoretically analyzed and numerically validated. If t(1v) and t(1vg) are conserved where t is optical thickness, v the single-scattering albedo, and g the asymmetry factor, it is possible that substantially different phase functions may give rise to similar radiances in both conservative and non-conservative scattering cases, particularly in the case of large optical thicknesses. In addition to theoretical analysis, this study uses operational ice cloud optical thickness retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 Collection5 (C5) and Collection 6 (C6) cloud property products to verify radiative similarity relations. It is found that, if the MODIS C5 and C6 ice cloud optical thickness values are multiplied by their respective (1wg)factors, the resultant products referred to as the effective optical thicknesses become similar with their ratio values around unity. Furthermore, the ratios of the C5 and C6 ice cloud effective optical thicknesses display an angular variation pattern similar to that of the corresponding ice cloud phase function ratios. The MODIS C5 and C6 values of ice cloud similarity parameter, defined as [(1w)(1(exp. 1/2)wg)]12, also tend to be similar.

Cloud Detection from Satellite Imagery: A Comparison of Expert-Generated and Automatically-Generated Decision Trees

NASA Technical Reports Server (NTRS)

Shiffman, Smadar

2004-01-01

Automated cloud detection and tracking is an important step in assessing global climate change via remote sensing. Cloud masks, which indicate whether individual pixels depict clouds, are included in many of the data products that are based on data acquired on- board earth satellites. Many cloud-mask algorithms have the form of decision trees, which employ sequential tests that scientists designed based on empirical astrophysics studies and astrophysics simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In this study we explored the potential benefits of automatically-learned decision trees for detecting clouds from images acquired using the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the NOAA-14 weather satellite of the National Oceanic and Atmospheric Administration. We constructed three decision trees for a sample of 8km-daily AVHRR data from 2000 using a decision-tree learning procedure provided within MATLAB(R), and compared the accuracy of the decision trees to the accuracy of the cloud mask. We used ground observations collected by the National Aeronautics and Space Administration Clouds and the Earth s Radiant Energy Systems S COOL project as the gold standard. For the sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks included in the AVHRR data product.

Results from the Two-Year Infrared Cloud Imager Deployment at ARM's NSA Observatory in Barrow, Alaska

NASA Astrophysics Data System (ADS)

Shaw, J. A.; Nugent, P. W.

2016-12-01

Ground-based longwave-infrared (LWIR) cloud imaging can provide continuous cloud measurements in the Arctic. This is of particular importance during the Arctic winter when visible wavelength cloud imaging systems cannot operate. This method uses a thermal infrared camera to observe clouds and produce measurements of cloud amount and cloud optical depth. The Montana State University Optical Remote Sensor Laboratory deployed an infrared cloud imager (ICI) at the Atmospheric Radiation Monitoring North Slope of Alaska site at Barrow, AK from July 2012 through July 2014. This study was used to both understand the long-term operation of an ICI in the Arctic and to study the consistency of the ICI data products in relation to co-located active and passive sensors. The ICI was found to have a high correlation (> 0.92) with collocated cloud instruments and to produce an unbiased data product. However, the ICI also detects thin clouds that are not detected by most operational cloud sensors. Comparisons with high-sensitivity actively sensed cloud products confirm the existence of these thin clouds. Infrared cloud imaging systems can serve a critical role in developing our understanding of cloud cover in the Arctic by provided a continuous annual measurement of clouds at sites of interest.

Identifying Meteorological Controls on Open and Closed Mesoscale Cellular Convection Associated with Marine Cold Air Outbreaks

NASA Astrophysics Data System (ADS)

McCoy, Isabel L.; Wood, Robert; Fletcher, Jennifer K.

2017-11-01

Mesoscale cellular convective (MCC) clouds occur in large-scale patterns over the ocean and have important radiative effects on the climate system. An examination of time-varying meteorological conditions associated with satellite-observed open and closed MCC clouds is conducted to illustrate the influence of large-scale meteorological conditions. Marine cold air outbreaks (MCAO) influence the development of open MCC clouds and the transition from closed to open MCC clouds. MCC neural network classifications on Moderate Resolution Imaging Spectroradiometer (MODIS) data for 2008 are collocated with Clouds and the Earth's Radiant Energy System (CERES) data and ERA-Interim reanalysis to determine the radiative effects of MCC clouds and their thermodynamic environments. Closed MCC clouds are found to have much higher albedo on average than open MCC clouds for the same cloud fraction. Three meteorological control metrics are tested: sea-air temperature difference (ΔT), estimated inversion strength (EIS), and a MCAO index (M). These predictive metrics illustrate the importance of atmospheric surface forcing and static stability for open and closed MCC cloud formation. Predictive sigmoidal relations are found between M and MCC cloud frequency globally and regionally: negative for closed MCC cloud and positive for open MCC cloud. The open MCC cloud seasonal cycle is well correlated with M, while the seasonality of closed MCC clouds is well correlated with M in the midlatitudes and EIS in the tropics and subtropics. M is found to best distinguish open and closed MCC clouds on average over shorter time scales. The possibility of a MCC cloud feedback is discussed.

Jupiter's High-Altitude Clouds

NASA Technical Reports Server (NTRS)

2007-01-01

The New Horizons Multispectral Visible Imaging Camera (MVIC) snapped this incredibly detailed picture of Jupiter's high-altitude clouds starting at 06:00 Universal Time on February 28, 2007, when the spacecraft was only 2.3 million kilometers (1.4 million miles) from the solar system's largest planet. Features as small as 50 kilometers (30 miles) are visible. The image was taken through a narrow filter centered on a methane absorption band near 890 nanometers, a considerably redder wavelength than what the eye can see. Images taken through this filter preferentially pick out clouds that are relatively high in the sky of this gas giant planet because sunlight at the wavelengths transmitted by the filter is completely absorbed by the methane gas that permeates Jupiter's atmosphere before it can reach the lower clouds.

The image reveals a range of diverse features. The south pole is capped with a haze of small particles probably created by the precipitation of charged particles into the polar regions during auroral activity. Just north of the cap is a well-formed anticyclonic vortex with rising white thunderheads at its core. Slightly north of the vortex are the tendrils of some rather disorganized storms and more pinpoint-like thunderheads. The dark 'measles' that appear a bit farther north are actually cloud-free regions where light is completely absorbed by the methane gas and essentially disappears from view. The wind action considerably picks up in the equatorial regions where giant plumes are stretched into a long wave pattern. Proceeding north of the equator, cirrus-like clouds are shredded by winds reaching speeds of up to 400 miles per hour, and more pinpoint-like thunderheads are visible. Although some of the famous belt and zone structure of Jupiter's atmosphere is washed out when viewed at this wavelength, the relatively thin North Temperate Belt shows up quite nicely, as does a series of waves just north of the belt. The north polar region of Jupiter in this image has a mottled appearance, and the scene is not as dynamic as the equatorial and south polar regions.

The intricate structures revealed in this image are exciting, but they are only part of the story. The New Horizons instruments have taken images of Jupiter at approximately 260 different wavelengths, providing essentially a three-dimensional view of Jupiter's atmosphere, since images at different wavelengths probe different altitudes. New Horizons is providing a wealth of data on this fascinating planet during this last close-up view of Jupiter until the middle of the next decade.

A synchronized particle image velocimetry and infrared thermography technique applied to convective mass transfer in champagne glasses

NASA Astrophysics Data System (ADS)

Beaumont, Fabien; Liger-Belair, Gérard; Bailly, Yannick; Polidori, Guillaume

2016-05-01

In champagne glasses, it was recently suggested that ascending bubble-driven flow patterns should be involved in the release of gaseous carbon dioxide (CO2) and volatile organic compounds. A key assumption was that the higher the velocity of the upward bubble-driven flow patterns in the liquid phase, the higher the volume fluxes of gaseous CO2 desorbing from the supersaturated liquid phase. In the present work, simultaneous monitoring of bubble-driven flow patterns within champagne glasses and gaseous CO2 escaping above the champagne surface was performed, through particle image velocimetry and infrared thermography techniques. Two quite emblematic types of champagne drinking vessels were investigated, namely a long-stemmed flute and a wide coupe. The synchronized use of both techniques proved that the cloud of gaseous CO2 escaping above champagne glasses strongly depends on the mixing flow patterns found in the liquid phase below.

Feasibility of Sensing Tropospheric Ozone with MODIS 9.6 Micron Observations

NASA Technical Reports Server (NTRS)

Prabhakara, C.; Iacovazzi, R., Jr.; Moon-Yoo, Jung

2004-01-01

With the infrared observations made by the Moderate Resolution Imaging Spectrometer (MODIS) on board the EOS-Aqua satellite, which include the 9.73 micron channel, a method is developed to deduce horizontal patterns of tropospheric ozone in cloud free conditions on a scale of about 100 km. It is assumed that on such small scale, at a given instant, horizontal changes in stratospheric ozone are small compared to that in the troposphere. From theoretical simulations it is found that uncertainties in the land surface emissivity and the vertical thermal stratification in the troposphere can lead to significant errors in the inferred tropospheric ozone. Because of this reason in order to derive horizontal patterns of tropospheric ozone in a given geographic area a tuning of this method is necessary with the help of a few dependent cases. After tuning, this method is applied to independent cases of MODIS data taken over Los Angeles basin in cloud free conditions to derive horizontal distribution of ozone in the troposphere. Preliminary results indicate that the derived patterns of ozone resemble crudely the patterns of surface ozone reported by EPA.

Reflections on current and future applications of multiangle imaging to aerosol and cloud remote sensing

NASA Astrophysics Data System (ADS)

Diner, David

2010-05-01

The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been collecting global Earth data from NASA's Terra satellite since February 2000. With its 9 along-track view angles, 4 spectral bands, intrinsic spatial resolution of 275 m, and stable radiometric and geometric calibration, no instrument that combines MISR's attributes has previously flown in space, nor is there is a similar capability currently available on any other satellite platform. Multiangle imaging offers several tools for remote sensing of aerosol and cloud properties, including bidirectional reflectance and scattering measurements, stereoscopic pattern matching, time lapse sequencing, and potentially, optical tomography. Current data products from MISR employ several of these techniques. Observations of the intensity of scattered light as a function of view angle and wavelength provide accurate measures of aerosol optical depths (AOD) over land, including bright desert and urban source regions. Partitioning of AOD according to retrieved particle classification and incorporation of height information improves the relationship between AOD and surface PM2.5 (fine particulate matter, a regulated air pollutant), constituting an important step toward a satellite-based particulate pollution monitoring system. Stereoscopic cloud-top heights provide a unique metric for detecting interannual variability of clouds and exceptionally high quality and sensitivity for detection and height retrieval for low-level clouds. Using the several-minute time interval between camera views, MISR has enabled a pole-to-pole, height-resolved atmospheric wind measurement system. Stereo imagery also makes possible global measurement of the injection heights and advection speeds of smoke plumes, volcanic plumes, and dust clouds, for which a large database is now available. To build upon what has been learned during the first decade of MISR observations, we are evaluating algorithm updates that not only refine retrieval accuracies but also include enhancements (e.g., finer spatial resolution) that would have been computationally prohibitive just ten years ago. In addition, we are developing technological building blocks for future sensors that enable broader spectral coverage, wider swath, and incorporation of high-accuracy polarimetric imaging. Prototype cameras incorporating photoelastic modulators have been constructed. To fully capitalize on the rich information content of the current and next-generation of multiangle imagers, several algorithmic paradigms currently employed need to be re-examined, e.g., the use of aerosol look-up tables, neglect of 3-D effects, and binary partitioning of the atmosphere into "cloudy" or "clear" designations. Examples of progress in algorithm and technology developments geared toward advanced application of multiangle imaging to remote sensing of aerosols and clouds will be presented.

Neptune Great Dark Spot in High Resolution

NASA Image and Video Library

1999-08-30

This photograph shows the last face on view of the Great Dark Spot that Voyager will make with the narrow angle camera. The image was shuttered 45 hours before closest approach at a distance of 2.8 million kilometers (1.7 million miles). The smallest structures that can be seen are of an order of 50 kilometers (31 miles). The image shows feathery white clouds that overlie the boundary of the dark and light blue regions. The pinwheel (spiral) structure of both the dark boundary and the white cirrus suggest a storm system rotating counterclockwise. Periodic small scale patterns in the white cloud, possibly waves, are short lived and do not persist from one Neptunian rotation to the next. This color composite was made from the clear and green filters of the narrow-angle camera. http://photojournal.jpl.nasa.gov/catalog/PIA00052

Determination of Cloud Base Height, Wind Velocity, and Short-Range Cloud Structure Using Multiple Sky Imagers Field Campaign Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Dong; Schwartz, Stephen E.; Yu, Dantong

Clouds are a central focus of the U.S. Department of Energy (DOE)’s Atmospheric System Research (ASR) program and Atmospheric Radiation Measurement (ARM) Climate Research Facility, and more broadly are the subject of much investigation because of their important effects on atmospheric radiation and, through feedbacks, on climate sensitivity. Significant progress has been made by moving from a vertically pointing (“soda-straw”) to a three-dimensional (3D) view of clouds by investing in scanning cloud radars through the American Recovery and Reinvestment Act of 2009. Yet, because of the physical nature of radars, there are key gaps in ARM's cloud observational capabilities. Formore » example, cloud radars often fail to detect small shallow cumulus and thin cirrus clouds that are nonetheless radiatively important. Furthermore, it takes five to twenty minutes for a cloud radar to complete a 3D volume scan and clouds can evolve substantially during this period. Ground-based stereo-imaging is a promising technique to complement existing ARM cloud observation capabilities. It enables the estimation of cloud coverage, height, horizontal motion, morphology, and spatial arrangement over an extended area of up to 30 by 30 km at refresh rates greater than 1 Hz (Peng et al. 2015). With fine spatial and temporal resolution of modern sky cameras, the stereo-imaging technique allows for the tracking of a small cumulus cloud or a thin cirrus cloud that cannot be detected by a cloud radar. With support from the DOE SunShot Initiative, the Principal Investigator (PI)’s team at Brookhaven National Laboratory (BNL) has developed some initial capability for cloud tracking using multiple distinctly located hemispheric cameras (Peng et al. 2015). To validate the ground-based cloud stereo-imaging technique, the cloud stereo-imaging field campaign was conducted at the ARM Facility’s Southern Great Plains (SGP) site in Oklahoma from July 15 to December 24. As shown in Figure 1, the cloud stereo-imaging system consisted of two inexpensive high-definition (HD) hemispheric cameras (each cost less than $1,500) and ARM’s Total Sky Imager (TSI). Together with other co-located ARM instrumentation, the campaign provides a promising opportunity to validate stereo-imaging-based cloud base height and, more importantly, to examine the feasibility of cloud thickness retrieval for low-view-angle clouds.« less

A CERES-like Cloud Property Climatology Using AVHRR Data

NASA Astrophysics Data System (ADS)

Minnis, P.; Bedka, K. M.; Yost, C. R.; Trepte, Q.; Bedka, S. T.; Sun-Mack, S.; Doelling, D.

2015-12-01

Clouds affect the climate system by modulating the radiation budget and distributing precipitation. Variations in cloud patterns and properties are expected to accompany changes in climate. The NASA Clouds and the Earth's Radiant Energy System (CERES) Project developed an end-to-end analysis system to measure broadband radiances from a radiometer and retrieve cloud properties from collocated high-resolution MODerate-resolution Imaging Spectroradiometer (MODIS) data to generate a long-term climate data record of clouds and clear-sky properties and top-of-atmosphere radiation budget. The first MODIS was not launched until 2000, so the current CERES record is only 15 years long at this point. The core of the algorithms used to retrieve the cloud properties from MODIS is based on the spectral complement of the Advanced Very High Resolution Radiometer (AVHRR), which has been aboard a string of satellites since 1978. The CERES cloud algorithms were adapted for application to AVHRR data and have been used to produce an ongoing CERES-like cloud property and surface temperature product that includes an initial narrowband-based radiation budget. This presentation will summarize this new product, which covers nearly 37 years, and its comparability with cloud parameters from CERES, CALIPSO, and other satellites. Examples of some applications of this dataset are given and the potential for generating a long-term radiation budget CDR is also discussed.

Weekly Cycle of Lightning and Associated Patterns of Rainfall, Cloud, and Aerosols over Korea and Adjacent Oceans during Boreal Summer

NASA Technical Reports Server (NTRS)

Kim, Ji-In; Kim, Kyu-Myong

2011-01-01

In this study, we analyze the weekly cycle of lightning over Korea and adjacent oceans and associated variations of aerosols, clouds, precipitation, and atmospheric circulations, using aerosol optical depth (AOD) from the NASA Moderate resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging SpectroRadiometer (MISR), cloud properties from MODIS, precipitation and storm height from Tropical Rainfall Measuring Mission (TRMM) satellite, and lightning data from the Korean Lightning Detection Network (KLDN) during 9-year from 2002 to 2010. Lightning data was divided into three approximately equal areas, land area of Korea, and two adjacent oceans, Yellow Sea and South Sea. Preliminary results show that the number of lightning increases during the middle of the week over Yellow Sea. AOD data also shows moderately significant midweek increase at about the same time as lightning peaks. These results are consistent with the recent studies showing the invigoration of storms with more ice hydrometeors by aerosols, and subsequently wash out of aerosols by rainfall. Frequency of lightning strokes tend to peak at weekend in land area and over South Sea, indicating local weekly anomalous circulation between land and adjacent ocean. On the other hand, lightning frequency over Yellow Sea appears to have very strong weekly cycle with midweek peak on around Wednesday. It is speculated that the midweek peak of lightning over Yellow Sea was related with aerosol transport from adjacent land area. AOD data also suggests midweek peak over Yellow Sea, however, the weekly cycle of AOD was not statistically significant. Changes in weekly cycle of lightning from pre-monsoon to monsoon season, as well as associated clouds and circulation patterns are also discussed.

Cloud Properties under Different Synoptic Circulations: Comparison of Radiosonde and Ground-Based Active Remote Sensing Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Jinqiang; Li, Jun; Xia, Xiangao

In this study, long-term (10 years) radiosonde-based cloud data are compared with the ground-based active remote sensing product under six prevailing large-scale synoptic patterns, i.e., cyclonic center (CC), weak pressure pattern (WP), the southeast bottom of cyclonic center (CB), cold front (CF), anticyclone edge (AE) and anticyclone center (AC) over the Southern Great Plains (SGP) site. The synoptic patterns are generated by applying the self-organizing map weather classification method to the daily National Centers for Environmental Protection mean sea level pressure records from the North American Regional Reanalysis. It reveals that the large-scale synoptic circulations can strongly influence the regionalmore » cloud formation, and thereby have impact on the consistency of cloud retrievals from the radiosonde and ground-based cloud product. The total cloud cover at the SGP site is characterized by the least in AC and the most in CF. The minimum and maximum differences between the two cloud methods are 10.3% for CC and 13.3% for WP. Compared to the synoptic patterns characterized by scattered cloudy and clear skies (AE and AC), the agreement of collocated cloud boundaries between the two cloud approaches tends to be better under the synoptic patterns dominated by overcast and cloudy skies (CC, WP and CB). The rainy and windy weather conditions in CF synoptic pattern influence the consistency of the two cloud retrieval methods associated with the limited capabilities inherent to the instruments. As a result, the cloud thickness distribution from the two cloud datasets compares favorably with each other in all synoptic patterns, with relative discrepancy of ≤0.3 km.« less

Cloud Properties under Different Synoptic Circulations: Comparison of Radiosonde and Ground-Based Active Remote Sensing Measurements

DOE PAGES

Zhang, Jinqiang; Li, Jun; Xia, Xiangao; ...

2016-11-28

In this study, long-term (10 years) radiosonde-based cloud data are compared with the ground-based active remote sensing product under six prevailing large-scale synoptic patterns, i.e., cyclonic center (CC), weak pressure pattern (WP), the southeast bottom of cyclonic center (CB), cold front (CF), anticyclone edge (AE) and anticyclone center (AC) over the Southern Great Plains (SGP) site. The synoptic patterns are generated by applying the self-organizing map weather classification method to the daily National Centers for Environmental Protection mean sea level pressure records from the North American Regional Reanalysis. It reveals that the large-scale synoptic circulations can strongly influence the regionalmore » cloud formation, and thereby have impact on the consistency of cloud retrievals from the radiosonde and ground-based cloud product. The total cloud cover at the SGP site is characterized by the least in AC and the most in CF. The minimum and maximum differences between the two cloud methods are 10.3% for CC and 13.3% for WP. Compared to the synoptic patterns characterized by scattered cloudy and clear skies (AE and AC), the agreement of collocated cloud boundaries between the two cloud approaches tends to be better under the synoptic patterns dominated by overcast and cloudy skies (CC, WP and CB). The rainy and windy weather conditions in CF synoptic pattern influence the consistency of the two cloud retrieval methods associated with the limited capabilities inherent to the instruments. As a result, the cloud thickness distribution from the two cloud datasets compares favorably with each other in all synoptic patterns, with relative discrepancy of ≤0.3 km.« less

The potential of using Landsat time-series to extract tropical dry forest phenology

NASA Astrophysics Data System (ADS)

Zhu, X.; Helmer, E.

2016-12-01

Vegetation phenology is the timing of seasonal developmental stages in plant life cycles. Due to the persistent cloud cover in tropical regions, current studies often use satellite data with high frequency, such as AVHRR and MODIS, to detect vegetation phenology. However, the spatial resolution of these data is from 250 m to 1 km, which does not have enough spatial details and it is difficult to relate to field observations. To produce maps of phenology at a finer spatial resolution, this study explores the feasibility of using Landsat images to detect tropical forest phenology through reconstructing a high-quality, seasonal time-series of images, and tested it in Mona Island, Puerto Rico. First, an automatic method was applied to detect cloud and cloud shadow, and a spatial interpolator was use to retrieve pixels covered by clouds, shadows, and SLC-off gaps. Second, enhanced vegetation index time-series derived from the reconstructed Landsat images were used to detect 11 phenology variables. Detected phenology is consistent with field investigations, and its spatial pattern is consistent with the rainfall distribution on this island. In addition, we may expect that phenology should correlate with forest biophysical attributes, so 47 plots with field measurement of biophysical attributes were used to indirectly validate the phenology product. Results show that phenology variables can explain a lot of variations in biophysical attributes. This study suggests that Landsat time-series has great potential to detect phenology in tropical areas.

Winter Cloud Streets, North Atlantic

NASA Image and Video Library

2017-12-08

NASA image acquired January 24, 2011 What do you get when you mix below-freezing air temperatures, frigid northwest winds from Canada, and ocean temperatures hovering around 39 to 40 degrees Fahrenheit (4 to 5 degrees Celsius)? Paved highways of clouds across the skies of the North Atlantic. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite collected this natural-color view of New England, the Canadian Maritimes, and coastal waters at 10:25 a.m. U.S. Eastern Standard Time on January 24, 2011. Lines of clouds stretch from northwest to southeast over the North Atlantic, while the relatively cloudless skies over land afford a peek at the snow that blanketed the Northeast just a few days earlier. Cloud streets form when cold air blows over warmer waters, while a warmer air layer—or temperature inversion—rests over top of both. The comparatively warm water of the ocean gives up heat and moisture to the cold air mass above, and columns of heated air—thermals—naturally rise through the atmosphere. As they hit the temperature inversion like a lid, the air rolls over like the circulation in a pot of boiling water. The water in the warm air cools and condenses into flat-bottomed, fluffy-topped cumulus clouds that line up parallel to the wind. Though they are easy to explain in a broad sense, cloud streets have a lot of mysteries on the micro scale. A NASA-funded researcher from the University of Wisconsin recently observed an unusual pattern in cloud streets over the Great Lakes. Cloud droplets that should have picked up moisture from the atmosphere and grown in size were instead shrinking as they moved over Lake Superior. Read more in an interview at What on Earth? NASA image by Jeff Schmaltz, MODIS Rapid Response Team, Goddard Space Flight Center. Caption by Michael Carlowicz. Instrument: Terra - MODIS Credit: NASA Earth Observatory NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Join us on Facebook

[Application of single-band brightness variance ratio to the interference dissociation of cloud for satellite data].

PubMed

Qu, Wei-ping; Liu, Wen-qing; Liu, Jian-guo; Lu, Yi-huai; Zhu, Jun; Qin, Min; Liu, Cheng

2006-11-01

In satellite remote-sensing detection, cloud as an interference plays a negative role in data retrieval. How to discern the cloud fields with high fidelity thus comes as a need to the following research. A new method rooting in atmospheric radiation characteristics of cloud layer, in the present paper, presents a sort of solution where single-band brightness variance ratio is used to detect the relative intensity of cloud clutter so as to delineate cloud field rapidly and exactly, and the formulae of brightness variance ratio of satellite image, image reflectance variance ratio, and brightness temperature variance ratio of thermal infrared image are also given to enable cloud elimination to produce data free from cloud interference. According to the variance of the penetrating capability for different spectra bands, an objective evaluation is done on cloud penetration of them with the factors that influence penetration effect. Finally, a multi-band data fusion task is completed using the image data of infrared penetration from cirrus nothus. Image data reconstruction is of good quality and exactitude to show the real data of visible band covered by cloud fields. Statistics indicates the consistency of waveband relativity with image data after the data fusion.

Efficiency and Flexibility of Fingerprint Scheme Using Partial Encryption and Discrete Wavelet Transform to Verify User in Cloud Computing.

PubMed

Yassin, Ali A

2014-01-01

Now, the security of digital images is considered more and more essential and fingerprint plays the main role in the world of image. Furthermore, fingerprint recognition is a scheme of biometric verification that applies pattern recognition techniques depending on image of fingerprint individually. In the cloud environment, an adversary has the ability to intercept information and must be secured from eavesdroppers. Unluckily, encryption and decryption functions are slow and they are often hard. Fingerprint techniques required extra hardware and software; it is masqueraded by artificial gummy fingers (spoof attacks). Additionally, when a large number of users are being verified at the same time, the mechanism will become slow. In this paper, we employed each of the partial encryptions of user's fingerprint and discrete wavelet transform to obtain a new scheme of fingerprint verification. Moreover, our proposed scheme can overcome those problems; it does not require cost, reduces the computational supplies for huge volumes of fingerprint images, and resists well-known attacks. In addition, experimental results illustrate that our proposed scheme has a good performance of user's fingerprint verification.

Efficiency and Flexibility of Fingerprint Scheme Using Partial Encryption and Discrete Wavelet Transform to Verify User in Cloud Computing

PubMed Central

Yassin, Ali A.

2014-01-01

Now, the security of digital images is considered more and more essential and fingerprint plays the main role in the world of image. Furthermore, fingerprint recognition is a scheme of biometric verification that applies pattern recognition techniques depending on image of fingerprint individually. In the cloud environment, an adversary has the ability to intercept information and must be secured from eavesdroppers. Unluckily, encryption and decryption functions are slow and they are often hard. Fingerprint techniques required extra hardware and software; it is masqueraded by artificial gummy fingers (spoof attacks). Additionally, when a large number of users are being verified at the same time, the mechanism will become slow. In this paper, we employed each of the partial encryptions of user's fingerprint and discrete wavelet transform to obtain a new scheme of fingerprint verification. Moreover, our proposed scheme can overcome those problems; it does not require cost, reduces the computational supplies for huge volumes of fingerprint images, and resists well-known attacks. In addition, experimental results illustrate that our proposed scheme has a good performance of user's fingerprint verification. PMID:27355051

Earth Observations taken by the Expedition 22 Crew

NASA Image and Video Library

2009-12-03

ISS022-E-005807 (3 Dec. 2009) --- Cloud formations and sunglint near Italy are featured in this image photographed by an Expedition 22 crew member on the International Space Station. This view depicts the Calabria region of southern Italy ? the toe of Italy?s ?boot? ? outlined by the Ionian and Tyrrhenian Seas to the southeast and northwest respectively. The water surfaces present a mirror-like appearance due to sunglint. This phenomenon is caused by sunlight reflecting off the water surface directly back towards the crew member aboard the space station. The ISS was located over northwestern Romania, approximately 1,040 kilometers to the northeast of Calabria, when this image was taken. The Calabrian peninsula appears shortened and distorted due to the high viewing angle from the station. Such imagery is termed oblique, indicating that the view is not looking directly downwards towards Earth?s surface from the ISS (known as a nadir view). This highly oblique view also highlights two distinct cloud patterns over the Calabrian interior. Patchy, highly textured cumulus clouds are present at lower altitudes, while grey altostratus clouds are elongated by prevailing winds at higher altitudes. The Strait of Messina, just visible at upper right, marks the boundary between the coastlines of Italy and the island of Sicily.

iMAGE cloud: medical image processing as a service for regional healthcare in a hybrid cloud environment.

PubMed

Liu, Li; Chen, Weiping; Nie, Min; Zhang, Fengjuan; Wang, Yu; He, Ailing; Wang, Xiaonan; Yan, Gen

2016-11-01

To handle the emergence of the regional healthcare ecosystem, physicians and surgeons in various departments and healthcare institutions must process medical images securely, conveniently, and efficiently, and must integrate them with electronic medical records (EMRs). In this manuscript, we propose a software as a service (SaaS) cloud called the iMAGE cloud. A three-layer hybrid cloud was created to provide medical image processing services in the smart city of Wuxi, China, in April 2015. In the first step, medical images and EMR data were received and integrated via the hybrid regional healthcare network. Then, traditional and advanced image processing functions were proposed and computed in a unified manner in the high-performance cloud units. Finally, the image processing results were delivered to regional users using the virtual desktop infrastructure (VDI) technology. Security infrastructure was also taken into consideration. Integrated information query and many advanced medical image processing functions-such as coronary extraction, pulmonary reconstruction, vascular extraction, intelligent detection of pulmonary nodules, image fusion, and 3D printing-were available to local physicians and surgeons in various departments and healthcare institutions. Implementation results indicate that the iMAGE cloud can provide convenient, efficient, compatible, and secure medical image processing services in regional healthcare networks. The iMAGE cloud has been proven to be valuable in applications in the regional healthcare system, and it could have a promising future in the healthcare system worldwide.

Snow cover detection algorithm using dynamic time warping method and reflectances of MODIS solar spectrum channels

NASA Astrophysics Data System (ADS)

Lee, Kyeong-sang; Choi, Sungwon; Seo, Minji; Lee, Chang suk; Seong, Noh-hun; Han, Kyung-Soo

2016-10-01

Snow cover is biggest single component of cryosphere. The Snow is covering the ground in the Northern Hemisphere approximately 50% in winter season and is one of climate factors that affects Earth's energy budget because it has higher reflectance than other land types. Also, snow cover has an important role about hydrological modeling and water resource management. For this reason, accurate detection of snow cover acts as an essential element for regional water resource management. Snow cover detection using satellite-based data have some advantages such as obtaining wide spatial range data and time-series observations periodically. In the case of snow cover detection using satellite data, the discrimination of snow and cloud is very important. Typically, Misclassified cloud and snow pixel can lead directly to error factor for retrieval of satellite-based surface products. However, classification of snow and cloud is difficult because cloud and snow have similar optical characteristics and are composed of water or ice. But cloud and snow has different reflectance in 1.5 1.7 μm wavelength because cloud has lower grain size and moisture content than snow. So, cloud and snow shows difference reflectance patterns change according to wavelength. Therefore, in this study, we perform algorithm for classifying snow cover and cloud with satellite-based data using Dynamic Time Warping (DTW) method which is one of commonly used pattern analysis such as speech and fingerprint recognitions and reflectance spectral library of snow and cloud. Reflectance spectral library is constructed in advance using MOD21km (MODIS Level1 swath 1km) data that their reflectance is six channels including 3 (0.466μm), 4 (0.554μm), 1 (0.647μm), 2 (0.857μm), 26 (1.382μm) and 6 (1.629μm). We validate our result using MODIS RGB image and MOD10 L2 swath (MODIS swath snow cover product). And we use PA (Producer's Accuracy), UA (User's Accuracy) and CI (Comparison Index) as validation criteria. The result of our study detect as snow cover in the several regions which are did not detected as snow in MOD10 L2 and detected as snow cover in MODIS RGB image. The result of our study can improve accuracy of other surface product such as land surface reflectance and land surface emissivity. Also it can use input data of hydrological modeling.

All-Sky Imaging of Skylight Polarization With Wildfire Smoke

NASA Astrophysics Data System (ADS)

Shaw, J. A.; Pust, N.; Forbes, E.; Dahl, L.

2014-12-01

We developed an all-sky imaging system for measuring skylight polarization in the visible and near-infrared spectral range. This instrument is used together with a multi-channel solar radiometer, an aerosol/cloud dual-polarization lidar, in-situ aerosol sensors, and a wide-angle thermal infrared cloud imager to study skylight polarization and its variation with changing aerosols, clouds, and underlying surface reflectance. All of these instruments except the lidar operate continuously outdoors. During August 2012, the continuously deployed instruments recorded the transition from relatively clean air to thick wildfire smoke. This presentation will summarize the temporal evolution of the aerosols and the resulting skylight polarization change as the smoke plume expanded and dissipated. During this event, the 500-nm zenith aerosol optical depth determined along the path to the Sun increased from 0.05 to 0.8 and the ground-level aerosol extinction coefficient at 530 nm wavelength increased from near 10 Mm-1 to 490 Mm-1. During the same time period, the maximum skylight polarization at 450 nm wavelength decreased from 0.7 to near 0.2. The skylight degree of linear polarization in an arc 90-degrees from the Sun was observed to transition from a nearly constant value across the arc to a highly spatially variable pattern because of the spatially nonuniform smoke plume.

AIRS Subpixel Cloud Characterization Using MODIS Cloud Products.

NASA Astrophysics Data System (ADS)

Li, Jun; Menzel, W. Paul; Sun, Fengying; Schmit, Timothy J.; Gurka, James

2004-08-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS's) Aqua satellite enable improved global monitoring of the distribution of clouds. MODIS is able to provide, at high spatial resolution (1 5 km), a cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud optical thickness (COT). AIRS is able to provide CTP, ECA, CPS, and COT at coarser spatial resolution (13.5 km at nadir) but with much better accuracy using its high-spectral-resolution measurements. The combined MODIS AIRS system offers the opportunity for improved cloud products over those possible from either system alone. The key steps for synergistic use of imager and sounder radiance measurements are 1) collocation in space and time and 2) imager cloud amount, type, and phase determination within the sounder pixel. The MODIS and AIRS measurements from the EOS Aqua satellite provide the opportunity to study the synergistic use of advanced imager and sounder measurements. As the first step, the MODIS classification procedure is applied to identify various surface and cloud types within an AIRS footprint. Cloud-layer information (lower, midlevel, or high clouds) and phase information (water, ice, or mixed-phase clouds) within the AIRS footprint are sorted and characterized using MODIS 1-km-spatial-resolution data. The combined MODIS and AIRS data for various scenes are analyzed to study the utility of the synergistic use of high-spatial-resolution imager products and high-spectral-resolution sounder radiance measurements. There is relevance to the optimal use of data from the Advanced Baseline Imager (ABI) and Hyperspectral Environmental Suite (HES) systems, which are to fly on the Geostationary Operational Environmental Satellite (GOES)-R.

Water Ice Clouds over the Northern Plains

NASA Technical Reports Server (NTRS)

2002-01-01

(Released 14 May 2002) The Science This image, centered near 48.5 N and 240.5 W, displays splotchy water ice clouds that obscure the northern lowland plains in the region where the Viking 2 spacecraft landed. This image is far enough north to catch the edge of the north polar hood that develops during the northern winter. This is a cap of water and carbon dioxide ice clouds that form over the Martian north pole. As Mars progresses into northern spring, the persistent north polar hood ice clouds will dissipate and the surface viewing conditions will improve greatly. As the season develops, an equatorial belt of water ice clouds will form. This belt of water ice clouds is as characteristic of the Martian climate as the southern hemisphere summer dust storm season. Seasons on Mars have a dramatic effect on the state of the dynamic Martian atmosphere. The Story Muted in an almost air-brushed manner, this image doesn't have the crispness that most THEMIS images have. That's because clouds were rising over the surface of the red planet on the day this picture was taken. Finding clouds on Mars might remind us of conditions here on Earth, but these Martian clouds are made of frozen water and frozen carbon dioxide -- in other words, clouds of ice and 'dry ice.' Strange as that may sound, the clouds seen here form on a pretty regular basis at the north Martian pole during its winter season. As springtime comes to the northern hemisphere of Mars (and fall comes to the southern), these clouds will slowly disappear, and a nice belt of water ice clouds will form around the equator. So, if you were a THEMIS camera aimer, that might tell you when your best viewing conditions for different areas on Mars would be. As interesting as clear pictures of Martian landforms are, however, you wouldn't want to bypass the weather altogether. Pictures showing seasonal shifts are great for scientists to study, because they reveal a lot about the patterns of the Martian climate and the circulation of the atmosphere. There are a lot of interesting global climate relationships to study. For example, when it's winter in the north of Mars and clouds like the ones in this image form, dust storms rage in the south of Mars, where it's summer. So why does Mars have these wild seasons? Like the Earth, Mars is tilted on its axis. As it travels in its orbit around the sun, the angle between the Earth's axis and the Earth-Sun line changes. That's true for Mars as well. As each point on Mars spins on the rotating red planet each day, the part of the cycle spent in sunlight (day) and shadow (night) just aren't equal because of these angles. When day is longer than night (summer) in the north, night is longer than day (winter) in the south. Half a year later, when Mars has traveled in its orbit to the other side of the sun, the situation is exactly reversed. All this sounds familiar to Earthlings, but there's yet one more difference. Mars is farther away from the sun than the Earth. That means it takes longer for Mars to make a trip around the sun in its orbit than the Earth does -- about twice as long, in fact. That means that the seasons on Mars also last twice as long!

Transitions of cloud-topped marine boundary layers characterized by AIRS, MODIS, and a large eddy simulation model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yue, Qing; Kahn, Brian; Xiao, Heng

2013-08-16

Cloud top entrainment instability (CTEI) is a hypothesized positive feedback between entrainment mixing and evaporative cooling near the cloud top. Previous theoretical and numerical modeling studies have shown that the persistence or breakup of marine boundary layer (MBL) clouds may be sensitive to the CTEI parameter. Collocated thermodynamic profile and cloud observations obtained from the Atmospheric Infrared Sounder (AIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments are used to quantify the relationship between the CTEI parameter and the cloud-topped MBL transition from stratocumulus to trade cumulus in the northeastern Pacific Ocean. Results derived from AIRS and MODIS are compared withmore » numerical results from the UCLA large eddy simulation (LES) model for both well-mixed and decoupled MBLs. The satellite and model results both demonstrate a clear correlation between the CTEI parameter and MBL cloud fraction. Despite fundamental differences between LES steady state results and the instantaneous snapshot type of observations from satellites, significant correlations for both the instantaneous pixel-scale observations and the long-term averaged spatial patterns between the CTEI parameter and MBL cloud fraction are found from the satellite observations and are consistent with LES results. This suggests the potential of using AIRS and MODIS to quantify global and temporal characteristics of the cloud-topped MBL transition.« less

MODIS Views Variations in Cloud Types

NASA Technical Reports Server (NTRS)

2002-01-01

This MODIS image, centered over the Great Lakes region in North America, shows a variety of cloud types. The clouds at the top of the image, colored pink, are cold, high-level snow and ice clouds, while the neon green clouds are lower-level water clouds. Because different cloud types reflect and emit radiant energy differently, scientists can use MODIS' unique data set to measure the sizes of cloud particles and distinguish between water, snow, and ice clouds. This scene was acquired on Feb. 24, 2000, and is a red, green, blue composite of bands 1, 6, and 31 (0.66, 1.6, and 11.0 microns, respectively). Image by Liam Gumley, Space Science and Engineering Center, University of Wisconsin-Madison

Point Cloud Generation from Aerial Image Data Acquired by a Quadrocopter Type Micro Unmanned Aerial Vehicle and a Digital Still Camera

PubMed Central

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems’ SOCET SET classical commercial photogrammetric software and another is built using Microsoft®’s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation. PMID:22368479

Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera.

PubMed

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems' SOCET SET classical commercial photogrammetric software and another is built using Microsoft(®)'s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation.

Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data

NASA Astrophysics Data System (ADS)

Thiele, Samuel T.; Grose, Lachlan; Samsu, Anindita; Micklethwaite, Steven; Vollgger, Stefan A.; Cruden, Alexander R.

2017-12-01

The advent of large digital datasets from unmanned aerial vehicle (UAV) and satellite platforms now challenges our ability to extract information across multiple scales in a timely manner, often meaning that the full value of the data is not realised. Here we adapt a least-cost-path solver and specially tailored cost functions to rapidly interpolate structural features between manually defined control points in point cloud and raster datasets. We implement the method in the geographic information system QGIS and the point cloud and mesh processing software CloudCompare. Using these implementations, the method can be applied to a variety of three-dimensional (3-D) and two-dimensional (2-D) datasets, including high-resolution aerial imagery, digital outcrop models, digital elevation models (DEMs) and geophysical grids. We demonstrate the algorithm with four diverse applications in which we extract (1) joint and contact patterns in high-resolution orthophotographs, (2) fracture patterns in a dense 3-D point cloud, (3) earthquake surface ruptures of the Greendale Fault associated with the Mw7.1 Darfield earthquake (New Zealand) from high-resolution light detection and ranging (lidar) data, and (4) oceanic fracture zones from bathymetric data of the North Atlantic. The approach improves the consistency of the interpretation process while retaining expert guidance and achieves significant improvements (35-65 %) in digitisation time compared to traditional methods. Furthermore, it opens up new possibilities for data synthesis and can quantify the agreement between datasets and an interpretation.

Automatic Matching of Large Scale Images and Terrestrial LIDAR Based on App Synergy of Mobile Phone

NASA Astrophysics Data System (ADS)

Xia, G.; Hu, C.

2018-04-01

The digitalization of Cultural Heritage based on ground laser scanning technology has been widely applied. High-precision scanning and high-resolution photography of cultural relics are the main methods of data acquisition. The reconstruction with the complete point cloud and high-resolution image requires the matching of image and point cloud, the acquisition of the homonym feature points, the data registration, etc. However, the one-to-one correspondence between image and corresponding point cloud depends on inefficient manual search. The effective classify and management of a large number of image and the matching of large image and corresponding point cloud will be the focus of the research. In this paper, we propose automatic matching of large scale images and terrestrial LiDAR based on APP synergy of mobile phone. Firstly, we develop an APP based on Android, take pictures and record related information of classification. Secondly, all the images are automatically grouped with the recorded information. Thirdly, the matching algorithm is used to match the global and local image. According to the one-to-one correspondence between the global image and the point cloud reflection intensity image, the automatic matching of the image and its corresponding laser radar point cloud is realized. Finally, the mapping relationship between global image, local image and intensity image is established according to homonym feature point. So we can establish the data structure of the global image, the local image in the global image, the local image corresponding point cloud, and carry on the visualization management and query of image.

Jupiter's Northern Hemisphere in True Color (Time Set 3)

NASA Technical Reports Server (NTRS)

1997-01-01

Mosaic of Jupiter's northern hemisphere between 10 and 50 degrees latitude. Jupiter's atmospheric circulation is dominated by alternating eastward and westward jets from equatorial to polar latitudes. The direction and speed of these jets in part determine the color and texture of the clouds seen in this mosaic. Also visible are several other common Jovian cloud features, including large white ovals, bright spots, dark spots, interacting vortices, and turbulent chaotic systems. The north-south dimension of each of the two interacting vortices in the upper half of the mosaic is about 3500 kilometers. This mosaic combines the violet (410 nanometers) and near infrared continuum (756 nanometers) filter images to create a mosaic similar to how Jupiter would appear to human eyes. Differences in coloration are due to the composition and abundance of trace chemicals in Jupiter's atmosphere.

North is at the top. The images are projected on a sphere, with features being foreshortened towards the north. The planetary limb runs along the right edge of the mosaic. Cloud patterns appear foreshortened as they approach the limb. The smallest resolved features are tens of kilometers in size. These images were taken on April 3, 1997, at a range of 1.4 million kilometers by the Solid State Imaging system (CCD) on NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Clementine Images of Earth and Moon

NASA Technical Reports Server (NTRS)

1997-01-01

During its flight and lunar orbit, the Clementine spacecraft returned images of the planet Earth and the Moon. This collection of UVVIS camera Clementine images shows the Earth from the Moon and 3 images of the Earth.

The image on the left shows the Earth as seen across the lunar north pole; the large crater in the foreground is Plaskett. The Earth actually appeared about twice as far above the lunar horizon as shown. The top right image shows the Earth as viewed by the UVVIS camera while Clementine was in transit to the Moon; swirling white cloud patterns indicate storms. The two views of southeastern Africa were acquired by the UVVIS camera while Clementine was in low Earth orbit early in the mission

Autumn at Titan's South Pole: The 220 cm-1 Cloud

NASA Astrophysics Data System (ADS)

Jennings, D. E.; Cottini, V.; Achterberg, R. K.; Anderson, C. M.; Flasar, F. M.; de Kok, R. J.; Teanby, N. A.; Coustenis, A.; Vinatier, S.

2015-10-01

Beginning in 2012 an atmospheric cloud known by its far-infrared emission has formed rapidly at Tit an's South Pole [1, 2]. The build-up of this condensate is a result of deepening temperatures and a gathering of gases as Winter approaches. Emission from the cloud in the south has been doubling each year since 2012, in contrast to the north where it has halved every 3.8 years since 2004. The morphology of the cloud in the south is quite different from that in the north. In the north, the cloud has extended over the whole polar region beyond 55 N, whereas in the south the cloud has been confined to within about 10 degrees of the pole. The cloud in the north has had the form of a uniform hood, whereas the southern cloud has been much more complex. A map from December 2014,recorded by the Composite Infrared Spectrometer (CIRS) on Cassini, showed the 220 cm-1 emission coming from a distinct ring with a maximum at about 80 S. In contrast, emissions from the gases HC3N, C4H2 and C6H6 peaked near the pole and had a ring at 70 S. The 220 cm-1 ring at 80 S coincided with the minimum in the gas emission pattern. The80 S condensate ring encompassed the vortex cloud seen by the Cassini Imaging Science Subsystem (ISS) and Visible and Infrared Mapping Spectrometer (VIMS)[3, 4]. Both the 220 cm-1 ring and the gas "bull's-eye" pattern were centered on a point that was shifted from the geographic South Pole by 4 degrees in the direction of the Sun. This corresponds to the overall tilt of Titan's atmosphere discovered from temperature maps early in the Cassini mission by Achterberg et al. [5]. The tilt may be reinforced by the presumably twice-yearly (north and south) spin-up of the atmosphere at the autumnal pole. The bull's-eye pattern of the gas emissions can be explained by the retrieved abundance distributions, which are maximum near the pole and decrease sharply toward lower latitudes, together with temperatures that are minimum at the pole and increase toward lower latitudes. The increasing temperatures overcome the decreasing gas abundances to produce emission in the narrow range around 70 S. This cannot, however, explain the maximum of emission at 80 S from the condensate ring. The coincidence at 80 S of the 220 cm-1 peak with the gas emission minimum may indicate where the condensation is taking place. The central, polar minimum in the cloud emission may be due to faster rain-out and smaller extinction cross-sections. Spectral maps from 2013-15 [6] show that the gas emission pattern has been evolving quickly, with noticeable changes from one flyby to the next (about one month). The bull's-eye structure appears to have been most prominent in early 2014 and by late 2014 the pattern was becoming more uniform. As Titan progresses through late southern Autumn we expect the morphology of the condensate cloud to take on a hood-like distribution similar to that in the north.

Fundamental Physics

NASA Image and Video Library

2003-02-09

This image depicts the formation of multiple whirlpools in a sodium gas cloud. Scientists who cooled the cloud and made it spin created the whirlpools in a Massachusetts Institute of Technology laboratory, as part of NASA-funded research. This process is similar to a phenomenon called starquakes that appear as glitches in the rotation of pulsars in space. MIT's Wolgang Ketterle and his colleagues, who conducted the research under a grant from the Biological and Physical Research Program through NASA's Jet Propulsion Laboratory, Pasadena, Calif., cooled the sodium gas to less than one millionth of a degree above absolute zero (-273 Celsius or -460 Fahrenheit). At such extreme cold, the gas cloud converts to a peculiar form of matter called Bose-Einstein condensate, as predicted by Albert Einstein and Satyendra Bose of India in 1927. No physical container can hold such ultra-cold matter, so Ketterle's team used magnets to keep the cloud in place. They then used a laser beam to make the gas cloud spin, a process Ketterle compares to stroking a ping-pong ball with a feather until it starts spirning. The spinning sodium gas cloud, whose volume was one- millionth of a cubic centimeter, much smaller than a raindrop, developed a regular pattern of more than 100 whirlpools.

Cloud Optical Depth Measured with Ground-Based, Uncooled Infrared Imagers

NASA Technical Reports Server (NTRS)

Shaw, Joseph A.; Nugent, Paul W.; Pust, Nathan J.; Redman, Brian J.; Piazzolla, Sabino

2012-01-01

Recent advances in uncooled, low-cost, long-wave infrared imagers provide excellent opportunities for remotely deployed ground-based remote sensing systems. However, the use of these imagers in demanding atmospheric sensing applications requires that careful attention be paid to characterizing and calibrating the system. We have developed and are using several versions of the ground-based "Infrared Cloud Imager (ICI)" instrument to measure spatial and temporal statistics of clouds and cloud optical depth or attenuation for both climate research and Earth-space optical communications path characterization. In this paper we summarize the ICI instruments and calibration methodology, then show ICI-derived cloud optical depths that are validated using a dual-polarization cloud lidar system for thin clouds (optical depth of approximately 4 or less).

Making Waves in the Sky off of Africa

NASA Image and Video Library

2017-12-08

On June 26, 2016, the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite acquired this natural-color image of cloud gravity waves off the coast of Angola and Namibia. “I [regularly] look at this area on Worldview because you quite often have these gravity waves,” said Bastiaan Van Diedenhoven, a researcher for Columbia University and NASA's Goddard Institute for Space Studies interested in cloud formations. “On this day, there was so much going on—so many different waves from different directions—that they really started interfering.” A distinctive criss-cross pattern formed in unbroken stretches hundreds of kilometers long. Similar to a boat’s wake, which forms as the water is pushed upward by the boat and pulled downward again by gravity, these clouds are formed by the rise and fall of colliding air columns. Off of west Africa, dry air coming off the Namib desert—after being cooled by the night—moves out under the balmy, moist air over the ocean and bumps it upwards. As the humid air rises to a higher altitude, the moisture condenses into droplets, forming clouds. Gravity rolls these newly formed clouds into a wave-like shape. When moist air goes up, it cools, and then gravity pushes it down again. As it plummets toward the earth, the moist air is pushed up again by the dry air. Repeated again and again, this process creates gravity waves. Clouds occur at the upward wave motions, while they evaporate at the downward motions. Such waves will often propagate in the morning and early afternoon, said Van Diedenhoven. During the course of the day, the clouds move out to sea and stretch out, as the dry air flowing off the land pushes the moist ocean air westward. NASA Earth Observatory image by Jesse Allen, using data from the Land Atmosphere Near real-time Capability for EOS (LANCE). via @NASAEarth go.nasa.gov/29Btxcy NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Creating cloud-free Landsat ETM+ data sets in tropical landscapes: cloud and cloud-shadow removal

Treesearch

Sebastián Martinuzzi; William A. Gould; Olga M. Ramos Gonzalez

2007-01-01

Clouds and cloud shadows are common features of visible and infrared remotelysensed images collected from many parts of the world, particularly in humid and tropical regions. We have developed a simple and semiautomated method to mask clouds and shadows in Landsat ETM+ imagery, and have developed a recent cloud-free composite of multitemporal images for Puerto Rico and...

Cloud top structure of Venus revealed by Subaru/COMICS mid-infrared images

NASA Astrophysics Data System (ADS)

Sato, T. M.; Sagawa, H.; Kouyama, T.; Mitsuyama, K.; Satoh, T.; Ohtsuki, S.; Ueno, M.; Kasaba, Y.; Nakamura, M.; Imamura, T.

2014-11-01

We have investigated the cloud top structure of Venus by analyzing ground-based images taken at the mid-infrared wavelengths of 8.66 μm and 11.34 μm. Venus at a solar phase angle of ∼90°, with the morning terminator in view, was observed by the Cooled Mid-Infrared Camera and Spectrometer (COMICS), mounted on the 8.2-m Subaru Telescope, during the period October 25-29, 2007. The disk-averaged brightness temperatures for the observation period are ∼230 K and ∼238 K at 8.66 μm and 11.34 μm, respectively. The obtained images with good signal-to-noise ratio and with high spatial resolution (∼200 km at the sub-observer point) provide several important findings. First, we present observational evidence, for the first time, of the possibility that the westward rotation of the polar features (the hot polar spots and the surrounding cold collars) is synchronized between the northern and southern hemispheres. Second, after high-pass filtering, the images reveal that streaks and mottled and patchy patterns are distributed over the entire disk, with typical amplitudes of ∼0.5 K, and vary from day to day. The detected features, some of which are similar to those seen in past UV images, result from inhomogeneities of both the temperature and the cloud top altitude. Third, the equatorial center-to-limb variations of brightness temperatures have a systematic day-night asymmetry, except those on October 25, that the dayside brightness temperatures are higher than the nightside brightness temperatures by 0-4 K under the same viewing geometry. Such asymmetry would be caused by the propagation of the migrating semidiurnal tide. Finally, by applying the lapse rates deduced from previous studies, we demonstrate that the equatorial center-to-limb curves in the two spectral channels give access to two parameters: the cloud scale height H and the cloud top altitude zc. The acceptable models for data on October 25 are obtained at H = 2.4-4.3 km and zc = 66-69 km; this supports previous results determined from spacecraft observations.

Artist's Rendering of Multiple Whirlpools in a Sodium Gas Cloud

NASA Technical Reports Server (NTRS)

2003-01-01

This image depicts the formation of multiple whirlpools in a sodium gas cloud. Scientists who cooled the cloud and made it spin created the whirlpools in a Massachusetts Institute of Technology laboratory, as part of NASA-funded research. This process is similar to a phenomenon called starquakes that appear as glitches in the rotation of pulsars in space. MIT's Wolgang Ketterle and his colleagues, who conducted the research under a grant from the Biological and Physical Research Program through NASA's Jet Propulsion Laboratory, Pasadena, Calif., cooled the sodium gas to less than one millionth of a degree above absolute zero (-273 Celsius or -460 Fahrenheit). At such extreme cold, the gas cloud converts to a peculiar form of matter called Bose-Einstein condensate, as predicted by Albert Einstein and Satyendra Bose of India in 1927. No physical container can hold such ultra-cold matter, so Ketterle's team used magnets to keep the cloud in place. They then used a laser beam to make the gas cloud spin, a process Ketterle compares to stroking a ping-pong ball with a feather until it starts spirning. The spinning sodium gas cloud, whose volume was one- millionth of a cubic centimeter, much smaller than a raindrop, developed a regular pattern of more than 100 whirlpools.

Hubble Provides Infrared View of Jupiter's Moon, Ring, and Clouds

NASA Technical Reports Server (NTRS)

1997-01-01

Probing Jupiter's atmosphere for the first time, the Hubble Space Telescope's new Near Infrared Camera and Multi-Object Spectrometer (NICMOS) provides a sharp glimpse of the planet's ring, moon, and high-altitude clouds.

The presence of methane in Jupiter's hydrogen- and helium-rich atmosphere has allowed NICMOS to plumb Jupiter's atmosphere, revealing bands of high-altitude clouds. Visible light observations cannot provide a clear view of these high clouds because the underlying clouds reflect so much visible light that the higher level clouds are indistinguishable from the lower layer. The methane gas between the main cloud deck and the high clouds absorbs the reflected infrared light, allowing those clouds that are above most of the atmosphere to appear bright. Scientists will use NICMOS to study the high altitude portion of Jupiter's atmosphere to study clouds at lower levels. They will then analyze those images along with visible light information to compile a clearer picture of the planet's weather. Clouds at different levels tell unique stories. On Earth, for example, ice crystal (cirrus) clouds are found at high altitudes while water (cumulus) clouds are at lower levels.

Besides showing details of the planet's high-altitude clouds, NICMOS also provides a clear view of the ring and the moon, Metis. Jupiter's ring plane, seen nearly edge-on, is visible as a faint line on the upper right portion of the NICMOS image. Metis can be seen in the ring plane (the bright circle on the ring's outer edge). The moon is 25 miles wide and about 80,000 miles from Jupiter.

Because of the near-infrared camera's narrow field of view, this image is a mosaic constructed from three individual images taken Sept. 17, 1997. The color intensity was adjusted to accentuate the high-altitude clouds. The dark circle on the disk of Jupiter (center of image) is an artifact of the imaging system.

This image and other images and data received from the Hubble Space Telescope are posted on the World Wide Web on the Space Telescope Science Institute home page at URL http://oposite.stsci.edu/pubinfo/

Plasma development in the accelerator of a 2-kJ focus discharge.

PubMed

Fischer, H; Haering, K H

1979-07-01

Optical image structures from early breakdown ( approximately 200 nsec) to focus formation (~1300 nsec) in 3 Torr hydrogen were studied by means of 2 image converter shutters having 50-nsec and 10-nsec exposure. Space charge limited cathode spots at the outer electrode (OE)-spoke-shaped positive columns across the gap-and an extended electron cloud along the center electrode (CE) determine the current flow during early breakdown. Ionization increases exponentially within the center gap plasma. This is separated from the CE by a pattern of anode drop filaments. Filament structures grow into the z-axis accelerated current sheath, which in addition carries the early spoke pattern. The sheath appears homogeneous after leaving the accelerator exit.

Cardiovascular imaging environment: will the future be cloud-based?

PubMed

Kawel-Boehm, Nadine; Bluemke, David A

2017-07-01

In cardiovascular CT and MR imaging large datasets have to be stored, post-processed, analyzed and distributed. Beside basic assessment of volume and function in cardiac magnetic resonance imaging e.g., more sophisticated quantitative analysis is requested requiring specific software. Several institutions cannot afford various types of software and provide expertise to perform sophisticated analysis. Areas covered: Various cloud services exist related to data storage and analysis specifically for cardiovascular CT and MR imaging. Instead of on-site data storage, cloud providers offer flexible storage services on a pay-per-use basis. To avoid purchase and maintenance of specialized software for cardiovascular image analysis, e.g. to assess myocardial iron overload, MR 4D flow and fractional flow reserve, evaluation can be performed with cloud based software by the consumer or complete analysis is performed by the cloud provider. However, challenges to widespread implementation of cloud services include regulatory issues regarding patient privacy and data security. Expert commentary: If patient privacy and data security is guaranteed cloud imaging is a valuable option to cope with storage of large image datasets and offer sophisticated cardiovascular image analysis for institutions of all sizes.

A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors

NASA Astrophysics Data System (ADS)

Sedano, Fernando; Kempeneers, Pieter; Strobl, Peter; Kucera, Jan; Vogt, Peter; Seebach, Lucia; San-Miguel-Ayanz, Jesús

2011-09-01

This study presents a novel cloud masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and cloud free composites at lower spatial resolution from almost simultaneously acquired dates. The methodology was tested taking SPOT4-HRVIR, SPOT5-HRG and IRS-LISS III as high resolution images and cloud free MODIS composites as reference images. The selected scenes included a wide range of cloud types and surface features. The resulting cloud masks were evaluated through visual comparison. They were also compared with ad-hoc independently generated cloud masks and with the automatic cloud cover assessment algorithm (ACCA). In general the results showed an agreement in detected clouds higher than 95% for clouds larger than 50 ha. The approach produced consistent results identifying and mapping clouds of different type and size over various land surfaces including natural vegetation, agriculture land, built-up areas, water bodies and snow.

Cloud-Induced Uncertainty for Visual Navigation

DTIC Science & Technology

2014-12-26

images at the pixel level. The result is a method that can overlay clouds with various structures on top of any desired image to produce realistic...cloud-shaped structures . The primary contribution of this research, however, is to investigate and quantify the errors in features due to clouds. The...of clouds types, this method does not emulate the true structure of clouds. An alternative popular modern method of creating synthetic clouds is known

Investigating Terrain Effects on Nearshore Cloud Evolution in Deepwave through Time-Lapse Photogrammetry

NASA Astrophysics Data System (ADS)

Osborne, T. C.; Billings, B. J.

2014-12-01

Stereo images of cloud patterns and nearshore waves upstream of the Southern Alps during the DEEPWAVE field campaign are presented through photogrammetric analysis. The photos highlighted in this case were taken in the afternoon of Friday, 13 June 2014. These photos were chosen because they may allow for focused analysis of terrain effects on cloud evolution. Stratocumulus and other cumuliform, as well as cirrus clouds were captured as the sun set over the Tasman Sea, one of the South Pacific Ocean's marginal seas. Breaks in the thin band of stratocumulus along the shoreline, as well as the total time for cloud layer dissipation are also of interest. A possible barrier jet causing the southward motion of the stratocumulus layer is also investigated. Views look northwest from Serpentine Road in Kumara Junction, South Island, New Zealand. An Integrated Sounding System (ISS) located at the Hokitika Airport was the primary source of vertical profiles. The upper air sounding closest to the shoot time and location, plotted from Hokitika's 11:05 UTC upsonde data, shows 10 mph NE winds near the surface. Images were taken on days with research flights over New Zealand from 2 June to 23 June 2014 to match DEEPWAVE objectives. On the night of 13 June 2014, NSF/NCAR's HIAPER GV research aircraft completed a flight from Christchurch over the South Island. This flight became known as Intensive Observing Period 3 (IOP 3) Sensitivity Flight. Methods applied in the Terrain-Induced Rotor Experiment (T-REX) by Grubišić and Grubišić (2007) were closely followed while capturing stereo photographic images. Two identical cameras were positioned with a separation baseline near 270 meters. Each camera was tilted upward approximately seven degrees and carefully positioned to capture parallel fields of view of the site. Developing clouds were captured using synchronized camera timers on a five second interval. Ultimately, cloud locations and measurements can be determined using the recorded GPS locations of the cameras. The Camera Calibration Toolbox available for MATLAB was used in order to perform these elaborate triangulation calculations.

3D cloud detection and tracking system for solar forecast using multiple sky imagers

DOE PAGES

Peng, Zhenzhou; Yu, Dantong; Huang, Dong; ...

2015-06-23

We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

The One to Multiple Automatic High Accuracy Registration of Terrestrial LIDAR and Optical Images

NASA Astrophysics Data System (ADS)

Wang, Y.; Hu, C.; Xia, G.; Xue, H.

2018-04-01

The registration of ground laser point cloud and close-range image is the key content of high-precision 3D reconstruction of cultural relic object. In view of the requirement of high texture resolution in the field of cultural relic at present, The registration of point cloud and image data in object reconstruction will result in the problem of point cloud to multiple images. In the current commercial software, the two pairs of registration of the two kinds of data are realized by manually dividing point cloud data, manual matching point cloud and image data, manually selecting a two - dimensional point of the same name of the image and the point cloud, and the process not only greatly reduces the working efficiency, but also affects the precision of the registration of the two, and causes the problem of the color point cloud texture joint. In order to solve the above problems, this paper takes the whole object image as the intermediate data, and uses the matching technology to realize the automatic one-to-one correspondence between the point cloud and multiple images. The matching of point cloud center projection reflection intensity image and optical image is applied to realize the automatic matching of the same name feature points, and the Rodrigo matrix spatial similarity transformation model and weight selection iteration are used to realize the automatic registration of the two kinds of data with high accuracy. This method is expected to serve for the high precision and high efficiency automatic 3D reconstruction of cultural relic objects, which has certain scientific research value and practical significance.

Lidar measurements of boundary layers, aerosol scattering and clouds during project FIFE

NASA Technical Reports Server (NTRS)

Eloranta, Edwin W. (Principal Investigator)

1995-01-01

A detailed account of progress achieved under this grant funding is contained in five journal papers. The titles of these papers are: The calculation of area-averaged vertical profiles of the horizontal wind velocity using volume imaging lidar data; Volume imaging lidar observation of the convective structure surrounding the flight path of an instrumented aircraft; Convective boundary layer mean depths, cloud base altitudes, cloud top altitudes, cloud coverages, and cloud shadows obtained from Volume Imaging Lidar data; An accuracy analysis of the wind profiles calculated from Volume Imaging Lidar data; and Calculation of divergence and vertical motion from volume-imaging lidar data. Copies of these papers form the body of this report.

Waves on Ice

Atmospheric Science Data Center

2013-04-16

article title:  Waves on White: Ice or Clouds?     View Larger ... like a wavy cloud pattern was actually a wavy pattern on the ice surface. One of MISR's cloud classification products, the Angular Signature ...

Invisible Cirrus Clouds

NASA Technical Reports Server (NTRS)

2002-01-01

The Moderate-resolution Imaging Spectroradiometer's (MODIS') cloud detection capability is so sensitive that it can detect clouds that would be indistinguishable to the human eye. This pair of images highlights MODIS' ability to detect what scientists call 'sub-visible cirrus.' The image on top shows the scene using data collected in the visible part of the electromagnetic spectrum-the part our eyes can see. Clouds are apparent in the center and lower right of the image, while the rest of the image appears to be relatively clear. However, data collected at 1.38um (lower image) show that a thick layer of previously undetected cirrus clouds obscures the entire scene. These kinds of cirrus are called 'sub-visible' because they can't be detected using only visible light. MODIS' 1.38um channel detects electromagnetic radiation in the infrared region of the spectrum. These images were made from data collected on April 4, 2000. Image courtesy Mark Gray, MODIS Atmosphere Team

Observations of Uranus and Neptune in Spanish Telescopes: Calar Alto/PlanetCam, WHT/Ingrid y GTC/Osiris

NASA Astrophysics Data System (ADS)

Hueso, R.; Sánchez-Lavega, A.; Ordonez-Etxeberria, I.; Rojas, J. F.; Pérez-Hoyos, S.; Mendikoa, I.

2017-03-01

The astronomical observation of the atmospheres of Uranus and Neptune poses unique challenges. Both planets are relatively dimm objects (visual magnitude of +5.3 and +7.7) and have small angular sizes (3.7” and 2.4” at opposition). Both worlds have atmospheres that are very dynamic, specially Neptune. These atmospheres are dominated by intense zonal winds that reach 450 m/s and where seasonal evolution changes the band patterns present in these planets. Thanks to the atmospheric methane gas, when observing Uranus and Neptune in near infrared wavelengths their upper clouds become well contrasted and bright and observations at different methane absorption bands allow to sample the atmosphere at different vertical layers. Both worlds are subject to the development of bright cloud patterns, some times of convective origin and whose activity can extend over weeks to several months or years. In the last few years we have surveyed the atmospheric activity of Uranus and Neptune with instruments able to improve the spatial resolution of the images beyond the limits impose by the atmospheric seeing. We use the Lucky Imaging technique (fast observation of several short-exposure frames combined with automatic selection of best frames and coregistration for stacking). We present image observations of Uranus and Neptune obtained with the instruments: OSIRIS at Grantecan as well as the AstraLux and PlanetCam UPV/EHU cameras on the 2.2m telescope at Calar Alto observatory. These observations are compared with other observations acquired by amateur astronomers able to obtain resolve cloud features in Uranus and Neptune. We compare these observations with images acquired with Adaptive Optics instruments at the William Herschel with the NAOMI+Ingrid instruments and Keck II and with Hubble Space Telescope images. We show the importance of surveying the atmospheric activity of these planets with a variety of telescopes. Two science cases are presented: The study of convective storms in Uranus in 2014 and the study of bright non convective features in Neptune in 2015.

Impact of decadal cloud variations on the Earth’s energy budget

DOE PAGES

Zhou, Chen; Zelinka, Mark D.; Klein, Stephen A.

2016-10-31

Feedbacks of clouds on climate change strongly influence the magnitude of global warming. Cloud feedbacks, in turn, depend on the spatial patterns of surface warming, which vary on decadal timescales. Therefore, the magnitude of the decadal cloud feedback could deviate from the long-term cloud feedback. We present climate model simulations to show that the global mean cloud feedback in response to decadal temperature fluctuations varies dramatically due to time variations in the spatial pattern of sea surface temperature. Here, we find that cloud anomalies associated with these patterns significantly modify the Earth’s energy budget. Specifically, the decadal cloud feedback betweenmore » the 1980s and 2000s is substantially more negative than the long-term cloud feedback. This is a result of cooling in tropical regions where air descends, relative to warming in tropical ascent regions, which strengthens low-level atmospheric stability. Under these conditions, low-level cloud cover and its reflection of solar radiation increase, despite an increase in global mean surface temperature. Our results suggest that sea surface temperature pattern-induced low cloud anomalies could have contributed to the period of reduced warming between 1998 and 2013, and o er a physical explanation of why climate sensitivities estimated from recently observed trends are probably biased low.« less

Impact of decadal cloud variations on the Earth’s energy budget

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Chen; Zelinka, Mark D.; Klein, Stephen A.

Feedbacks of clouds on climate change strongly influence the magnitude of global warming. Cloud feedbacks, in turn, depend on the spatial patterns of surface warming, which vary on decadal timescales. Therefore, the magnitude of the decadal cloud feedback could deviate from the long-term cloud feedback. We present climate model simulations to show that the global mean cloud feedback in response to decadal temperature fluctuations varies dramatically due to time variations in the spatial pattern of sea surface temperature. Here, we find that cloud anomalies associated with these patterns significantly modify the Earth’s energy budget. Specifically, the decadal cloud feedback betweenmore » the 1980s and 2000s is substantially more negative than the long-term cloud feedback. This is a result of cooling in tropical regions where air descends, relative to warming in tropical ascent regions, which strengthens low-level atmospheric stability. Under these conditions, low-level cloud cover and its reflection of solar radiation increase, despite an increase in global mean surface temperature. Our results suggest that sea surface temperature pattern-induced low cloud anomalies could have contributed to the period of reduced warming between 1998 and 2013, and o er a physical explanation of why climate sensitivities estimated from recently observed trends are probably biased low.« less

Impact of decadal cloud variations on the Earth's energy budget

NASA Astrophysics Data System (ADS)

Zhou, Chen; Zelinka, Mark D.; Klein, Stephen A.

2016-12-01

Feedbacks of clouds on climate change strongly influence the magnitude of global warming. Cloud feedbacks, in turn, depend on the spatial patterns of surface warming, which vary on decadal timescales. Therefore, the magnitude of the decadal cloud feedback could deviate from the long-term cloud feedback. Here we present climate model simulations to show that the global mean cloud feedback in response to decadal temperature fluctuations varies dramatically due to time variations in the spatial pattern of sea surface temperature. We find that cloud anomalies associated with these patterns significantly modify the Earth's energy budget. Specifically, the decadal cloud feedback between the 1980s and 2000s is substantially more negative than the long-term cloud feedback. This is a result of cooling in tropical regions where air descends, relative to warming in tropical ascent regions, which strengthens low-level atmospheric stability. Under these conditions, low-level cloud cover and its reflection of solar radiation increase, despite an increase in global mean surface temperature. These results suggest that sea surface temperature pattern-induced low cloud anomalies could have contributed to the period of reduced warming between 1998 and 2013, and offer a physical explanation of why climate sensitivities estimated from recently observed trends are probably biased low.

Biomedical image analysis and processing in clouds

NASA Astrophysics Data System (ADS)

Bednarz, Tomasz; Szul, Piotr; Arzhaeva, Yulia; Wang, Dadong; Burdett, Neil; Khassapov, Alex; Chen, Shiping; Vallotton, Pascal; Lagerstrom, Ryan; Gureyev, Tim; Taylor, John

2013-10-01

Cloud-based Image Analysis and Processing Toolbox project runs on the Australian National eResearch Collaboration Tools and Resources (NeCTAR) cloud infrastructure and allows access to biomedical image processing and analysis services to researchers via remotely accessible user interfaces. By providing user-friendly access to cloud computing resources and new workflow-based interfaces, our solution enables researchers to carry out various challenging image analysis and reconstruction tasks. Several case studies will be presented during the conference.

Simulation of Optical Properties and Direct and Indirect Radiative Effects of Smoke Aerosols Over Marine Stratocumulus Clouds During Summer 2008 in California With the Regional Climate Model RegCM

NASA Astrophysics Data System (ADS)

Mallet, M.; Solmon, F.; Roblou, L.; Peers, F.; Turquety, S.; Waquet, F.; Jethva, H.; Torres, O.

2017-10-01

The regional climate model RegCM has been modified to better account for the climatic effects of biomass-burning particles. Smoke aerosols are represented by new tracers with consistent radiative and hygroscopic properties to simulate the direct radiative forcing (DRF), and a new parameterization has been integrated for relating the droplet number concentration to the aerosol concentration for marine stratocumulus clouds (Sc). RegCM has been tested during the summer of 2008 over California, when extreme concentration of smoke, together with the presence of Sc, is observed. This work indicates that significant aerosol optical depth (AOD) ( 1-2 at 550 nm) is related to the intense 2008 fires. Compared to Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer, the regional pattern of RegCM AOD is well represented although the magnitude is lower than satellite observations. Comparisons with Polarization and Directionality of Earth Reflectances (POLDER) above-clouds aerosol optical depth (ACAOD) show the ability of RegCM to simulate realistic ACAOD during the transport of smoke above the Pacific Ocean. The simulated single scattering albedo is 0.90 (at 550 nm) near biomass-burning sources, consistent with OMI and POLDER, and smoke leads to shortwave heating rates 1.5-2°K d-1. RegCM is not able to correctly resolve the daily patterns in cloud properties notably due to its coarse horizontal resolutions. However, the changes in the sign of the DRF at top of atmosphere (TOA) (negative to positive) from clear-sky to all-sky conditions is well simulated. Finally, the "aerosol-cloud" parameterization allows simulating an increase of the cloud optical depth for significant concentrations, leading to large perturbations of radiative fluxes at TOA.

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 1: A cloud ensemble/radiative parameterization for sensor response (report version)

NASA Technical Reports Server (NTRS)

Olson, William S.; Raymond, William H.

1990-01-01

The physical retrieval of geophysical parameters based upon remotely sensed data requires a sensor response model which relates the upwelling radiances that the sensor observes to the parameters to be retrieved. In the retrieval of precipitation water contents from satellite passive microwave observations, the sensor response model has two basic components. First, a description of the radiative transfer of microwaves through a precipitating atmosphere must be considered, because it is necessary to establish the physical relationship between precipitation water content and upwelling microwave brightness temperature. Also the spatial response of the satellite microwave sensor (or antenna pattern) must be included in the description of sensor response, since precipitation and the associated brightness temperature field can vary over a typical microwave sensor resolution footprint. A 'population' of convective cells, as well as stratiform clouds, are simulated using a computationally-efficient multi-cylinder cloud model. Ensembles of clouds selected at random from the population, distributed over a 25 km x 25 km model domain, serve as the basis for radiative transfer calculations of upwelling brightness temperatures at the SSM/I frequencies. Sensor spatial response is treated explicitly by convolving the upwelling brightness temperature by the domain-integrated SSM/I antenna patterns. The sensor response model is utilized in precipitation water content retrievals.

Eruption of Shiveluch Volcano, Kamchatka Peninsula

NASA Technical Reports Server (NTRS)

2007-01-01

On March 29, 2007, the Shiveluch Volcano on the Russian Federation's Kamchatka Peninsula erupted. According to the Alaska Volcano Observatory the volcano underwent an explosive eruption between 01:50 and 2:30 UTC, sending an ash cloud skyward roughly 9,750 meters (32,000 feet), based on visual estimates. The Moderate Resolution Imaging Spectroradiometer (MODIS) flying onboard NASA's Aqua satellite took this picture at 02:00 UTC on March 29. The top image shows the volcano and its surroundings. The bottom image shows a close-up view of the volcano at 250 meters per pixel. Satellites often capture images of volcanic ash plumes, but usually as the plumes are blowing away. Plumes have been observed blowing away from Shiveluch before. This image, however, is different. At the time the Aqua satellite passed overhead, the eruption was recent enough (and the air was apparently still enough) that the ash cloud still hovered above the summit. In this image, the bulbous cloud casts its shadow northward over the icy landscape. Volcanic ash eruptions inject particles into Earth's atmosphere. Substantial eruptions of light-reflecting particles can reduce temperatures and even affect atmospheric circulation. Large eruptions impact climate patterns for years. A massive eruption of the Tambora Volcano in Indonesia in 1815, for instance, earned 1816 the nickname 'the year without a summer.' Shiveluch is a stratovolcano--a steep-sloped volcano composed of alternating layers of solidified ash, hardened lava, and volcanic rocks. One of Kamchatka's largest volcanoes, it sports a summit reaching 3,283 meters (10,771 feet). Shiveluch is also one of the peninsula's most active volcanoes, with an estimated 60 substantial eruptions in the past 10,000 years.

Jupiter's Equatorial Region in a Methane band (Time set 1)

NASA Technical Reports Server (NTRS)

1997-01-01

Mosaic of Jupiter's equatorial region at 727 nanometers (nm). The mosaic covers an area of 34,000 kilometers by 22,000 kilometers. Light at 727 nm is moderately absorbed by atmospheric methane. This image shows the features of Jupiter's main visible cloud deck and upper tropospheric haze, with higher features enhanced in brightness over lower features. The dark region near the center of the mosaic is an equatorial 'hotspot' similar to the Galileo Probe entry site. These features are holes in the bright, reflective, equatorial cloud layer where warmer thermal emission from Jupiter's deep atmosphere can pass through. The circulation patterns observed here along with the composition measurements from the Galileo Probe suggest that dry air may be converging and sinking over these regions, maintaining their cloud-free appearance. The bright oval in the upper right of the mosaic as well as the other smaller bright features are examples of upwelling of moist air and condensation.

North is at the top. The mosaic covers latitudes 1 to 19 degrees and is centered at longitude 336 degrees West. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers by the Solid State Imaging system aboard NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Jupiter's Equatorial Region in a Methane band (Time set 4)

NASA Technical Reports Server (NTRS)

1997-01-01

Mosaic of Jupiter's equatorial region at 727 nanometers (nm). The mosaic covers an area of 34,000 kilometers by 22,000 kilometers. Light at 727 nm is moderately absorbed by atmospheric methane. This image shows the features of Jupiter's main visible cloud deck and upper-tropospheric haze, with higher features enhanced in brightness over lower features. The dark region near the center of the mosaic is an equatorial 'hotspot' similar to the Galileo Probe entry site. These features are holes in the bright, reflective, equatorial cloud layer where warmer thermal emission from Jupiter's deep atmosphere can pass through. The circulation patterns observed here along with the composition measurements from the Galileo Probe suggest that dry air may be converging and sinking over these regions, maintaining their cloud-free appearance. The bright oval in the upper right of the mosaic as well as the other smaller bright features are examples of upwelling of moist air and condensation.

North is at the top. The mosaic covers latitudes 1 to 19 degrees and is centered at longitude 336 degrees West. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers by the Solid State Imaging system aboard NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Remote sensing image segmentation based on Hadoop cloud platform

NASA Astrophysics Data System (ADS)

Li, Jie; Zhu, Lingling; Cao, Fubin

2018-01-01

To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

Intercomparison study and optical asphericity measurements of small ice particles in the CERN CLOUD experiment

NASA Astrophysics Data System (ADS)

Nichman, Leonid; Järvinen, Emma; Dorsey, James; Connolly, Paul; Duplissy, Jonathan; Fuchs, Claudia; Ignatius, Karoliina; Sengupta, Kamalika; Stratmann, Frank; Möhler, Ottmar; Schnaiter, Martin; Gallagher, Martin

2017-09-01

Optical probes are frequently used for the detection of microphysical cloud particle properties such as liquid and ice phase, size and morphology. These properties can eventually influence the angular light scattering properties of cirrus clouds as well as the growth and accretion mechanisms of single cloud particles. In this study we compare four commonly used optical probes to examine their response to small cloud particles of different phase and asphericity. Cloud simulation experiments were conducted at the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at European Organisation for Nuclear Research (CERN). The chamber was operated in a series of multi-step adiabatic expansions to produce growth and sublimation of ice particles at super- and subsaturated ice conditions and for initial temperatures of -30, -40 and -50 °C. The experiments were performed for ice cloud formation via homogeneous ice nucleation. We report the optical observations of small ice particles in deep convection and in situ cirrus simulations. Ice crystal asphericity deduced from measurements of spatially resolved single particle light scattering patterns by the Particle Phase Discriminator mark 2 (PPD-2K, Karlsruhe edition) were compared with Cloud and Aerosol Spectrometer with Polarisation (CASPOL) measurements and image roundness captured by the 3View Cloud Particle Imager (3V-CPI). Averaged path light scattering properties of the simulated ice clouds were measured using the Scattering Intensity Measurements for the Optical detectioN of icE (SIMONE) and single particle scattering properties were measured by the CASPOL. We show the ambiguity of several optical measurements in ice fraction determination of homogeneously frozen ice in the case where sublimating quasi-spherical ice particles are present. Moreover, most of the instruments have difficulties of producing reliable ice fraction if small aspherical ice particles are present, and all of the instruments cannot separate perfectly spherical ice particles from supercooled droplets. Correlation analysis of bulk averaged path depolarisation measurements and single particle measurements of these clouds showed higher R2 values at high concentrations and small diameters, but these results require further confirmation. We find that none of these instruments were able to determine unambiguously the phase of the small particles. These results have implications for the interpretation of atmospheric measurements and parametrisations for modelling, particularly for low particle number concentration clouds.

Digital all-sky polarization imaging of partly cloudy skies.

PubMed

Pust, Nathan J; Shaw, Joseph A

2008-12-01

Clouds reduce the degree of linear polarization (DOLP) of skylight relative to that of a clear sky. Even thin subvisual clouds in the "twilight zone" between clouds and aerosols produce a drop in skylight DOLP long before clouds become visible in the sky. In contrast, the angle of polarization (AOP) of light scattered by a cloud in a partly cloudy sky remains the same as in the clear sky for most cases. In unique instances, though, select clouds display AOP signatures that are oriented 90 degrees from the clear-sky AOP. For these clouds, scattered light oriented parallel to the scattering plane dominates the perpendicularly polarized Rayleigh-scattered light between the instrument and the cloud. For liquid clouds, this effect may assist cloud particle size identification because it occurs only over a relatively limited range of particle radii that will scatter parallel polarized light. Images are shown from a digital all-sky-polarization imager to illustrate these effects. Images are also shown that provide validation of previously published theories for weak (approximately 2%) polarization parallel to the scattering plane for a 22 degrees halo.

Clouds above the Martin Limb: Viking observations

NASA Technical Reports Server (NTRS)

Martin, L. J.; Baum, W. A.; Wasserman, L. H.; Kreidl, T. J.

1984-01-01

Whenever Viking Orbiter images included the limb of Mars, they recorded one or more layers of clouds above the limb. The height above the limb and the brightness (reflectivity) of these clouds were determined in a selected group of these images. Normalized individual brightness profiles of three separate traverses across the limb of each image are shown. The most notable finding is that some of these clouds can be very high. Many reach heights of over 60 km, and several are over 70 km above the limb. Statistically, the reflectivity of the clouds increases with phase angle. Reflectivity and height both appear to vary with season, but the selected images spanned only one Martian year, so the role of seasons cannot be isolated. Limb clouds in red-filter images tend to be brighter than violet-filter images, but both season and phase appear to be more dominant factors. Due to the limited sample available, the possible influences of latitude and longitude are less clear. The layering of these clouds ranges from a single layer to five or more layers. Reflectivity gradients range from smooth and gentle to steep and irregular.

A weighted variational gradient-based fusion method for high-fidelity thin cloud removal of Landsat images

NASA Astrophysics Data System (ADS)

Huang, Wei; Chen, Xiu; Wang, Yueyun

2018-03-01

Landsat data are widely used in various earth observations, but the clouds interfere with the applications of the images. This paper proposes a weighted variational gradient-based fusion method (WVGBF) for high-fidelity thin cloud removal of Landsat images, which is an improvement of the variational gradient-based fusion (VGBF) method. The VGBF method integrates the gradient information from the reference band into visible bands of cloudy image to enable spatial details and remove thin clouds. The VGBF method utilizes the same gradient constraints to the entire image, which causes the color distortion in cloudless areas. In our method, a weight coefficient is introduced into the gradient approximation term to ensure the fidelity of image. The distribution of weight coefficient is related to the cloud thickness map. The map is built on Independence Component Analysis (ICA) by using multi-temporal Landsat images. Quantitatively, we use R value to evaluate the fidelity in the cloudless regions and metric Q to evaluate the clarity in the cloud areas. The experimental results indicate that the proposed method has the better ability to remove thin cloud and achieve high fidelity.

Brute Force Matching Between Camera Shots and Synthetic Images from Point Clouds

NASA Astrophysics Data System (ADS)

Boerner, R.; Kröhnert, M.

2016-06-01

3D point clouds, acquired by state-of-the-art terrestrial laser scanning techniques (TLS), provide spatial information about accuracies up to several millimetres. Unfortunately, common TLS data has no spectral information about the covered scene. However, the matching of TLS data with images is important for monoplotting purposes and point cloud colouration. Well-established methods solve this issue by matching of close range images and point cloud data by fitting optical camera systems on top of laser scanners or rather using ground control points. The approach addressed in this paper aims for the matching of 2D image and 3D point cloud data from a freely moving camera within an environment covered by a large 3D point cloud, e.g. a 3D city model. The key advantage of the free movement affects augmented reality applications or real time measurements. Therefore, a so-called real image, captured by a smartphone camera, has to be matched with a so-called synthetic image which consists of reverse projected 3D point cloud data to a synthetic projection centre whose exterior orientation parameters match the parameters of the image, assuming an ideal distortion free camera.

Mesoscale wake clouds in Skylab pictures.

NASA Technical Reports Server (NTRS)

Fujita, T. T.; Tecson, J. J.

1974-01-01

The recognition of cloud patterns formed in the wake of orographic obstacles was investigated using pictures from Skylab, for the purpose of estimating atmospheric motions. The existence of ship-wake-type wave clouds in contrast to vortex sheets were revealed during examination of the pictures, and an attempt was made to characterize the pattern of waves as well as the transition between waves and vortices. Examples of mesoscale cloud patterns which were analyzed photogrammetrically and meteorologically are presented.

CloudSat Overflight of Hurricane Bud

NASA Image and Video Library

2006-07-13

The image at the top of figure 1 is from a geostationary imager. The colors relate to the temperature of the clouds. The higher the clouds, the lower the temperature. The highest, coldest clouds are located near the center of the hurricane.

4-D cloud properties from passive satellite data and applications to resolve the flight icing threat to aircraft

NASA Astrophysics Data System (ADS)

Smith, William L., Jr.

The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This thesis develops new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft in a wide range of cloud conditions. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS, the satellite icing detection and intensity accuracies are found to be about 90% and 70%, respectively. Mean differences between the imager IWC retrievals with those from CloudSat and Calipso are less than 30%. This level of closure in the cloud water budget can only be achieved by correcting for errors in the imager retrievals due to the simplifying but poor assumption that deep optically thick clouds are single-phase and vertically homogeneous. When applied to geostationary satellite data, the profiling method provides a real-time characterization of clouds in 4-D. This research should improve the utility of satellite imager data for quantitatively diagnosing and predicting clouds and their effects in weather and climate applications.

Apollo 9 Mission image - Earth Observation - Anticyclonic cloud pattern

NASA Image and Video Library

1969-03-03

AS09-23-3592 (3-13 March 1969) --- Cyclonic storm system, located 1,200 miles north of Hawaii, as photographed from the Apollo 9 spacecraft during its 10-day, Earth-orbital space mission. This picture was made on the 124th revolution of Apollo 9. This cyclonic storm system can also be seen in the ESSA-7 photograph taken on March 11, 1969.

Discriminating satellite IR anomalies associated with the MS 7.1 Yushu earthquake in China

NASA Astrophysics Data System (ADS)

Qin, Kai; Wu, Lixin; Zheng, Shuo; Ma, Weiyu

2018-03-01

In the process of exploring pre-earthquake thermal anomalies using satellite infrared data, Blackett et al. (2011) found that the previously reported anomalies before the 2001 Mw 7.7 Gujarat earthquake, in India, were related to positive biases caused by data gaps due to cloud cover and mosaicing of neighboring orbits of MODIS satellite data. They supposed that such effects could also be responsible for other cases. We noted a strip-shaped TIR anomaly on March 17th, 2010, 28 days before the Ms. 7.1 Yushu earthquake (Qin et al., 2011). Here we again investigate multi-year infrared satellite data in different bands to discriminate whether the anomaly is associated with the earthquake, or is only bias caused by the data gaps. From the water vapor images, we find lots of clouds that have TIR anomalies. However, on the cloudiness background, there is an obvious strip-shaped gap matching the tectonic faults almost perfectly. In particular, the animation loops of hourly water vapor images show that the cloud kept moving from west to east, while they never covered the strip-shaped gap. We consider that the cloud with this special spatial pattern should have implied the abnormal signals associated with the seismogenic process. Based on current physical models, the satellite IR anomalies both on TIR and water vapor bands can qualitatively be explained using synthetic mechanisms.

Clementine Images of Earth and Moon

NASA Image and Video Library

1999-06-12

During its flight and lunar orbit, NASA’s Clementine spacecraft returned images of the planet Earth and the Moon. This collection of UVVIS camera Clementine images shows the Earth from the Moon and 3 images of the Earth. The image on the left shows the Earth as seen across the lunar north pole; the large crater in the foreground is Plaskett. The Earth actually appeared about twice as far above the lunar horizon as shown. The top right image shows the Earth as viewed by the UVVIS camera while Clementine was in transit to the Moon; swirling white cloud patterns indicate storms. The two views of southeastern Africa were acquired by the UVVIS camera while Clementine was in low Earth orbit early in the mission. http://photojournal.jpl.nasa.gov/catalog/PIA00432

Automatic Cloud Detection from Multi-Temporal Satellite Images: Towards the Use of PLÉIADES Time Series

NASA Astrophysics Data System (ADS)

Champion, N.

2012-08-01

Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images) and is based on a region-growing procedure. Seeds (corresponding to clouds) are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images). Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011). In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.

Evaluation of Methods for Coregistration and Fusion of Rpas-Based 3d Point Clouds and Thermal Infrared Images

NASA Astrophysics Data System (ADS)

Hoegner, L.; Tuttas, S.; Xu, Y.; Eder, K.; Stilla, U.

2016-06-01

This paper discusses the automatic coregistration and fusion of 3d point clouds generated from aerial image sequences and corresponding thermal infrared (TIR) images. Both RGB and TIR images have been taken from a RPAS platform with a predefined flight path where every RGB image has a corresponding TIR image taken from the same position and with the same orientation with respect to the accuracy of the RPAS system and the inertial measurement unit. To remove remaining differences in the exterior orientation, different strategies for coregistering RGB and TIR images are discussed: (i) coregistration based on 2D line segments for every single TIR image and the corresponding RGB image. This method implies a mainly planar scene to avoid mismatches; (ii) coregistration of both the dense 3D point clouds from RGB images and from TIR images by coregistering 2D image projections of both point clouds; (iii) coregistration based on 2D line segments in every single TIR image and 3D line segments extracted from intersections of planes fitted in the segmented dense 3D point cloud; (iv) coregistration of both the dense 3D point clouds from RGB images and from TIR images using both ICP and an adapted version based on corresponding segmented planes; (v) coregistration of both image sets based on point features. The quality is measured by comparing the differences of the back projection of homologous points in both corrected RGB and TIR images.

Preliminary Results from the First Deployment of a Tethered-Balloon Cloud Particle Imager Instrument Package in Arctic Stratus Clouds at Ny-Alesund

NASA Astrophysics Data System (ADS)

Lawson, P.; Stamnes, K.; Stamnes, J.; Zmarzly, P.; O'Connor, D.; Koskulics, J.; Hamre, B.

2008-12-01

A tethered balloon system specifically designed to collect microphysical data in mixed-phase clouds was deployed in Arctic stratus clouds during May 2008 near Ny-Alesund, Svalbard, at 79 degrees North Latitude. This is the first time a tethered balloon system with a cloud particle imager (CPI) that records high-resolution digital images of cloud drops and ice particles has been operated in cloud. The custom tether supplies electrical power to the instrument package, which in addition to the CPI houses a 4-pi short-wavelength radiometer and a met package that measures temperature, humidity, pressure, GPS position, wind speed and direction. The instrument package was profiled vertically through cloud up to altitudes of 1.6 km. Since power was supplied to the instrument package from the ground, it was possible to keep the balloon package aloft for extended periods of time, up to 9 hours at Ny- Ålesund, which was limited only by crew fatigue. CPI images of cloud drops and the sizes, shapes and degree of riming of ice particles are shown throughout vertical profiles of Arctic stratus clouds. The images show large regions of mixed-phase cloud from -8 to -2 C. The predominant ice crystal habits in these regions are needles and aggregates of needles. The amount of ice in the mixed-phase clouds varied considerably and did not appear to be a function of temperature. On some occasions, ice was observed near cloud base at -2 C with supercooled cloud above to - 8 C that was devoid of ice. Measurements of shortwave radiation are also presented. Correlations between particle distributions and radiative measurements will be analyzed to determine the effect of these Arctic stratus clouds on radiative forcing.

Cloud cameras at the Pierre Auger Observatory

NASA Astrophysics Data System (ADS)

Winnick, Michael G.

2010-06-01

This thesis presents the results of measurements made by infrared cloud cameras installed at the Pierre Auger Observatory in Argentina. These cameras were used to record cloud conditions during operation of the observatory's fluorescence detectors. As cloud may affect the measurement of fluorescence from cosmic ray extensive air showers, the cloud cameras provide a record of which measurements have been interfered with by cloud. Several image processing algorithms were developed, along with a methodology for the detection of cloud within infrared images taken by the cloud cameras. A graphical user interface (GUI) was developed to expediate this, as a large number of images need to be checked for cloud. A cross-check between images recorded by three of the observatory's cloud cameras is presented, along with a comparison with independent cloud measurements made by LIDAR. Despite the cloud cameras and LIDAR observing different areas of the sky, a good agreement is observed in the measured cloud fraction between the two instruments, particularly on very clear and overcast nights. Cloud information recorded by the cloud cameras, with cloud height information measured by the LIDAR, was used to identify those extensive air showers that were obscured by cloud. These events were used to study the effectiveness of standard quality cuts at removing cloud afflicted events. Of all of the standard quality cuts studied in this thesis, the LIDAR cloud fraction cut was the most effective at preferentially removing cloud obscured events. A 'cloudy pixel' veto is also presented, whereby cloud obscured measurements are excluded during the standard hybrid analysis, and new extensive air shower reconstructed parameters determined. The application of such a veto would provide a slight increase to the number of events available for higher level analysis.

Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Menzel, W. Paul; Ackerman, Steven A.; Hubanks, Paul A.

2012-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched aboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. A comprehensive set of remote sensing algorithms for the retrieval of cloud physical and optical properties have enabled over twelve years of continuous observations of cloud properties from Terra and over nine years from Aqua. The archived products from these algorithms include 1 km pixel-level (Level-2) and global gridded Level-3 products. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. Results include the latitudinal distribution of cloud optical and radiative properties for both liquid water and ice clouds, as well as latitudinal distributions of cloud top pressure and cloud top temperature. MODIS finds the cloud fraction, as derived by the cloud mask, is nearly identical during the day and night, with only modest diurnal variation. Globally, the cloud fraction derived by the MODIS cloud mask is approx.67%, with somewhat more clouds over land during the afternoon and less clouds over ocean in the afternoon, with very little difference in global cloud cover between Terra and Aqua. Overall, cloud fraction over land is approx.55%, with a distinctive seasonal cycle, whereas the ocean cloudiness is much higher, around 72%, with much reduced seasonal variation. Cloud top pressure and temperature have distinct spatial and temporal patterns, and clearly reflect our understanding of the global cloud distribution. High clouds are especially prevalent over the northern hemisphere continents between 30 and 50 . Aqua and Terra have comparable zonal cloud top pressures, with Aqua having somewhat higher clouds (cloud top pressures lower by 100 hPa) over land due to afternoon deep convection. The coldest cloud tops (colder than 230 K) generally occur over Antarctica and the high clouds in the tropics (ITCZ and the deep convective clouds over the western tropical Pacific and Indian sub-continent).

ERTS-1 views the Great Lakes

NASA Technical Reports Server (NTRS)

Lyons, W. A.; Pease, S. R.

1973-01-01

The meteorological content of ERTS images, particularly mesoscale effects of the Great Lakes and air pollution dispersion is summarized. Summertime lake breeze frontal clouds and various winter lake-effect convection patterns and snow squalls are revealed in great detail. A clear-cut spiral vortex over southern Lake Michigan is related to a record early snow storm in the Chicago area. Marked cloud changes induced by orographic and frictional effects on Lake Michigan's lee shore snow squalls are seen. The most important finding, however, is a clear-cut example of alterations in cumulus convection by anthropogenic condensation and/or ice nuclei from northern Indiana steel mills during a snow squall situation. Jet aircraft condensation trails are also found with surprising frequency.

ARC-1990-A91-2013

NASA Image and Video Library

1990-02-14

Range : 1.4 to 2 million miles These are enhanced versions of four views of Venus taken by Galileo's Solid State Imaging System. The pictures in the top row were taken about 4 and 5 days after closest approach, and those in the bottom row 6 days after closest approach, 2 hours apart. These show the faint Venusian cloud features vary clearly. A high-pass filter way applied to bring out broader global variations in tone. The bright polar hoods are a well-known feature of Venus. Of particular interest to planetary atmospheric scientists are the complex cloud patterns near the equator, in the vicinity of the bright subsolar point, where convection is most prevalent.

ARC-1990-AC91-2004

NASA Image and Video Library

1990-02-14

Range : 1.7 million miles This colorized picture of Venus was taken about 6 days after Galileo's closest approach to the planet. It has been colorized to a bluish hue to emphasize subtle contrasts in the cloud markings and to indicate that it was taken through a violet filter. Features in the sulfuric acid clouds near the top of the planet's atmosphere are most prominent in violet and ultraviolet light. This image shows the east-to-west-trending cloud banding and the brighter polar hoods familiar from past studies of Venus. The features are embedded in winds that flow from east to west at about 230 mph. The smallest features visible are about 45 miles across. An intriguing filamentary dark pattern is seen immediately left of the bright region at the subsolar point (equatorial 'noon'). North is at the top and the evening terminator is to the left.

A Medical Image Backup Architecture Based on a NoSQL Database and Cloud Computing Services.

PubMed

Santos Simões de Almeida, Luan Henrique; Costa Oliveira, Marcelo

2015-01-01

The use of digital systems for storing medical images generates a huge volume of data. Digital images are commonly stored and managed on a Picture Archiving and Communication System (PACS), under the DICOM standard. However, PACS is limited because it is strongly dependent on the server's physical space. Alternatively, Cloud Computing arises as an extensive, low cost, and reconfigurable resource. However, medical images contain patient information that can not be made available in a public cloud. Therefore, a mechanism to anonymize these images is needed. This poster presents a solution for this issue by taking digital images from PACS, converting the information contained in each image file to a NoSQL database, and using cloud computing to store digital images.

Jupiter Eruptions

NASA Technical Reports Server (NTRS)

2008-01-01

[figure removed for brevity, see original site] Click on the image for high resolution image of Nature Cover

Detailed analysis of two continent-sized storms that erupted in Jupiter's atmosphere in March 2007 shows that Jupiter's internal heat plays a significant role in generating atmospheric disturbances. Understanding these outbreaks could be the key to unlock the mysteries buried in the deep Jovian atmosphere, say astronomers.

This visible-light image is from NASA's Hubble Space Telescope taken on May 11, 2007. It shows the turbulent pattern generated by the two plumes on the upper left part of Jupiter.

Understanding these phenomena is important for Earth's meteorology where storms are present everywhere and jet streams dominate the atmospheric circulation. Jupiter is a natural laboratory where atmospheric scientists study the nature and interplay of the intense jets and severe atmospheric phenomena.

According to the analysis, the bright plumes were storm systems triggered in Jupiter's deep water clouds that moved upward in the atmosphere vi gorously and injected a fresh mixture of ammonia ice and water about 20 miles (30 kilometers) above the visible clouds. The storms moved in the peak of a jet stream in Jupiter's atmosphere at 375 miles per hour (600 kilometers per hour). Models of the disturbance indicate that the jet stream extends deep in the buried atmosphere of Jupiter, more than 60 miles (approximately100 kilometers) below the cloud tops where most sunlight is absorbed.

High Speed Imaging of Cavitation around Dental Ultrasonic Scaler Tips.

PubMed

Vyas, Nina; Pecheva, Emilia; Dehghani, Hamid; Sammons, Rachel L; Wang, Qianxi X; Leppinen, David M; Walmsley, A Damien

2016-01-01

Cavitation occurs around dental ultrasonic scalers, which are used clinically for removing dental biofilm and calculus. However it is not known if this contributes to the cleaning process. Characterisation of the cavitation around ultrasonic scalers will assist in assessing its contribution and in developing new clinical devices for removing biofilm with cavitation. The aim is to use high speed camera imaging to quantify cavitation patterns around an ultrasonic scaler. A Satelec ultrasonic scaler operating at 29 kHz with three different shaped tips has been studied at medium and high operating power using high speed imaging at 15,000, 90,000 and 250,000 frames per second. The tip displacement has been recorded using scanning laser vibrometry. Cavitation occurs at the free end of the tip and increases with power while the area and width of the cavitation cloud varies for different shaped tips. The cavitation starts at the antinodes, with little or no cavitation at the node. High speed image sequences combined with scanning laser vibrometry show individual microbubbles imploding and bubble clouds lifting and moving away from the ultrasonic scaler tip, with larger tip displacement causing more cavitation.

High Speed Imaging of Cavitation around Dental Ultrasonic Scaler Tips

PubMed Central

Vyas, Nina; Pecheva, Emilia; Dehghani, Hamid; Sammons, Rachel L.; Wang, Qianxi X.; Leppinen, David M.; Walmsley, A. Damien

2016-01-01

Cavitation occurs around dental ultrasonic scalers, which are used clinically for removing dental biofilm and calculus. However it is not known if this contributes to the cleaning process. Characterisation of the cavitation around ultrasonic scalers will assist in assessing its contribution and in developing new clinical devices for removing biofilm with cavitation. The aim is to use high speed camera imaging to quantify cavitation patterns around an ultrasonic scaler. A Satelec ultrasonic scaler operating at 29 kHz with three different shaped tips has been studied at medium and high operating power using high speed imaging at 15,000, 90,000 and 250,000 frames per second. The tip displacement has been recorded using scanning laser vibrometry. Cavitation occurs at the free end of the tip and increases with power while the area and width of the cavitation cloud varies for different shaped tips. The cavitation starts at the antinodes, with little or no cavitation at the node. High speed image sequences combined with scanning laser vibrometry show individual microbubbles imploding and bubble clouds lifting and moving away from the ultrasonic scaler tip, with larger tip displacement causing more cavitation. PMID:26934340

Mystery #21 Answer

Atmospheric Science Data Center

2013-04-22

article title:  MISR Mystery Image Quiz #21: Actinoform Clouds ... This mystery concerns a particular type of cloud, one example of which was imaged by the Multi-angle Imaging SpectroRadiometer (MISR) ... ) These clouds are commonly tracked using propeller-driven research aircraft. Answer: C is True. The weather satellite, TIROS ...

Cloud Detection of Optical Satellite Images Using Support Vector Machine

NASA Astrophysics Data System (ADS)

Lee, Kuan-Yi; Lin, Chao-Hung

2016-06-01

Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection accuracy of the proposed method is better than related methods.

On the Cloud Observations in JAXA's Next Coming Satellite Missions

NASA Technical Reports Server (NTRS)

Nakajima, Takashi Y.; Nagao, Takashi M.; Letu, Husi; Ishida, Haruma; Suzuki, Kentaroh

2012-01-01

The use of JAXA's next generation satellites, the EarthCARE and the GCOM-C, for observing overall cloud systems on the Earth is discussed. The satellites will be launched in the middle of 2010-era and contribute for observing aerosols and clouds in terms of climate change, environment, weather forecasting, and cloud revolution process study. This paper describes the role of such satellites and how to use the observing data showing concepts and some sample viewgraphs. Synergistic use of sensors is a key of the study. Visible to infrared bands are used for cloudy and clear discriminating from passively obtained satellite images. Cloud properties such as the cloud optical thickness, the effective particle radii, and the cloud top temperature will be retrieved from visible to infrared wavelengths of imagers. Additionally, we are going to combine cloud properties obtained from passive imagers and radar reflectivities obtained from an active radar in order to improve our understanding of cloud evolution process. This is one of the new techniques of satellite data analysis in terms of cloud sciences in the next decade. Since the climate change and cloud process study have mutual beneficial relationship, a multispectral wide-swath imagers like the GCOM-C SGLI and a comprehensive observation package of cloud and aerosol like the EarthCARE are both necessary.

Anaglyph, Landsat overlay Honolulu, Hawaii

NASA Technical Reports Server (NTRS)

2000-01-01

Honolulu, on the island of Oahu, is a large and growing urban area with limited space and water resources. This anaglyph, combining a Landsat image with SRTM topography, shows how the topography controls the urban growth pattern, causes cloud formation, and directs the rainfall runoff pattern. Red/blue glasses are required to see the 3-D effect. Features of interest in this scene include Diamond Head (an extinct volcano on the right side of the image), Waikiki Beach (just left of Diamond Head), the Punchbowl National Cemetary (another extinct volcano, left of center), downtown Honolulu and Honolulu harbor (lower left of center), and offshore reef patterns. The slopes of the Koolau mountain range are seen in the upper half of the image. Clouds commonly hang above ridges and peaks of the Hawaiian Islands, and in this rendition appear draped directly on the mountains. The clouds are actually about 1000 meters (3300 feet) above sea level. High resolution topographic and image data allow ecologists and planners to assess the effects of urban development on the sensitive ecosystems in tropical regions.

This anaglyph was generated using topographic data from the Shuttle Radar Topography Mission, combined with a Landsat 7 satellite image collected coincident with the SRTM mission. The topography data are used to create two differing perspectives of a single image, one perspective for each eye. Each point in the image is shifted slightly, depending on its elevation. When viewed through special glasses, the result is a vertically exaggerated view of the Earth's surface in its full three dimensions. Anaglyph glasses cover the left eye with a red filter and cover the right eye with a blue filter. The United States Geological Survey's Earth Resources Observations Systems (EROS) DataCenter, Sioux Falls, South Dakota, provided the Landsat data.

The Shuttle Radar Topography Mission (SRTM), launched on February 11, 2000, uses the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. The mission is designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, an additional C-band imaging antenna and improved tracking and navigation devices. The mission is a cooperative project between the National Aeronautics and Space Administration (NASA), the National Imagery and Mapping Agency (NIMA) and the German (DLR) and Italian (ASI) space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Earth Science Enterprise, Washington, DC.

Size: 18 by 28 kilometers (11 by 17 miles) Location: 21.3 deg. North lat., 157.9 deg. West lon. Orientation: North toward upper left Original Data Resolution: SRTM, 30 meters (99 feet); Landsat, 15 meters (50 feet) Date Acquired: SRTM, February 18, 2000; Landsat February 12, 2000

Automated detection of Martian water ice clouds: the Valles Marineris

NASA Astrophysics Data System (ADS)

Ogohara, Kazunori; Munetomo, Takafumi; Hatanaka, Yuji; Okumura, Susumu

2016-10-01

We need to extract water ice clouds from the large number of Mars images in order to reveal spatial and temporal variations of water ice cloud occurrence and to meteorologically understand climatology of water ice clouds. However, visible images observed by Mars orbiters for several years are too many to visually inspect each of them even though the inspection was limited to one region. Therefore, an automated detection algorithm of Martian water ice clouds is necessary for collecting ice cloud images efficiently. In addition, it may visualize new aspects of spatial and temporal variations of water ice clouds that we have never been aware. We present a method for automatically evaluating the presence of Martian water ice clouds using difference images and cross-correlation distributions calculated from blue band images of the Valles Marineris obtained by the Mars Orbiter Camera onboard the Mars Global Surveyor (MGS/MOC). We derived one subtracted image and one cross-correlation distribution from two reflectance images. The difference between the maximum and the average, variance, kurtosis, and skewness of the subtracted image were calculated. Those of the cross-correlation distribution were also calculated. These eight statistics were used as feature vectors for training Support Vector Machine, and its generalization ability was tested using 10-fold cross-validation. F-measure and accuracy tended to be approximately 0.8 if the maximum in the normalized reflectance and the difference of the maximum and the average in the cross-correlation were chosen as features. In the process of the development of the detection algorithm, we found many cases where the Valles Marineris became clearly brighter than adjacent areas in the blue band. It is at present unclear whether the bright Valles Marineris means the occurrence of water ice clouds inside the Valles Marineris or not. Therefore, subtracted images showing the bright Valles Marineris were excluded from the detection of water ice clouds

Sahara Dust Cloud

NASA Technical Reports Server (NTRS)

2005-01-01

[figure removed for brevity, see original site] Dust Particles Click on the image for Quicktime movie from 7/15-7/24

A continent-sized cloud of hot air and dust originating from the Sahara Desert crossed the Atlantic Ocean and headed towards Florida and the Caribbean. A Saharan Air Layer, or SAL, forms when dry air and dust rise from Africa's west coast and ride the trade winds above the Atlantic Ocean.

These dust clouds are not uncommon, especially during the months of July and August. They start when weather patterns called tropical waves pick up dust from the desert in North Africa, carry it a couple of miles into the atmosphere and drift westward.

In a sequence of images created by data acquired by the Earth-orbiting Atmospheric Infrared Sounder ranging from July 15 through July 24, we see the distribution of the cloud in the atmosphere as it swirls off of Africa and heads across the ocean to the west. Using the unique silicate spectral signatures of dust in the thermal infrared, AIRS can detect the presence of dust in the atmosphere day or night. This detection works best if there are no clouds present on top of the dust; when clouds are present, they can interfere with the signal, making it much harder to detect dust as in the case of July 24, 2005.

In the Quicktime movie, the scale at the bottom of the images shows +1 for dust definitely detected, and ranges down to -1 for no dust detected. The plots are averaged over a number of AIRS observations falling within grid boxes, and so it is possible to obtain fractional numbers. [figure removed for brevity, see original site] Total Water Vapor in the Atmosphere Around the Dust Cloud Click on the image for Quicktime movie

The dust cloud is contained within a dry adiabatic layer which originates over the Sahara Desert. This Saharan Air Layer (SAL) advances Westward over the Atlantic Ocean, overriding the cool, moist air nearer the surface. This burst of very dry air is visible in the AIRS retrieved total water vapor product as a region of depressed water vapor (brown in the images) migrating slowly Westward toward the Caribbean. The SAL phenomenon inhibits the formation of tropical cyclones and thus has given the West Indies and the East Coast of the US a respite from hurricanes.

The Atmospheric Infrared Sounder Experiment, with its visible, infrared, and microwave detectors, provides a three-dimensional look at Earth's weather. Working in tandem, the three instruments can make simultaneous observations all the way down to the Earth's surface, even in the presence of heavy clouds. With more than 2,000 channels sensing different regions of the atmosphere, the system creates a global, 3-D map of atmospheric temperature and humidity and provides information on clouds, greenhouse gases, and many other atmospheric phenomena. The AIRS Infrared Sounder Experiment flies onboard NASA's Aqua spacecraft and is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., under contract to NASA. JPL is a division of the California Institute of Technology in Pasadena.

Spatial and temporal patterns of cloud cover and fog inundation in coastal California: Ecological implications

USGS Publications Warehouse

Rastogi, Bharat; Williams, A. Park; Fischer, Douglas T.; Iacobellis, Sam F.; McEachern, A. Kathryn; Carvalho, Leila; Jones, Charles Leslie; Baguskas, Sara A.; Still, Christopher J.

2016-01-01

The presence of low-lying stratocumulus clouds and fog has been known to modify biophysical and ecological properties in coastal California where forests are frequently shaded by low-lying clouds or immersed in fog during otherwise warm and dry summer months. Summer fog and stratus can ameliorate summer drought stress and enhance soil water budgets, and often have different spatial and temporal patterns. Here we use remote sensing datasets to characterize the spatial and temporal patterns of cloud cover over California’s northern Channel Islands. We found marine stratus to be persistent from May through September across the years 2001-2012. Stratus clouds were both most frequent and had the greatest spatial extent in July. Clouds typically formed in the evening, and dissipated by the following early afternoon. We present a novel method to downscale satellite imagery using atmospheric observations and discriminate patterns of fog from those of stratus and help explain patterns of fog deposition previously studied on the islands. The outcomes of this study contribute significantly to our ability to quantify the occurrence of coastal fog at biologically meaningful spatial and temporal scales that can improve our understanding of cloud-ecosystem interactions, species distributions and coastal ecohydrology.

a Cloud Boundary Detection Scheme Combined with Aslic and Cnn Using ZY-3, GF-1/2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Guo, Z.; Li, C.; Wang, Z.; Kwok, E.; Wei, X.

2018-04-01

Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN) is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC) method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.

Satellite Shows West Coast "June Gloom" and Actinoform clouds

NASA Image and Video Library

2017-12-08

NOAA's GOES-15 satellite captured the southern California "June Gloom" on June 10, 2013. That's a weather pattern that creates cloudy, overcast skies and cool temperatures. The "June Gloom" of low lying stratus clouds form over the ocean and can be pushed to coastal areas by wind. It usually happens off the west coast of California during the late spring and early summer. As for the "seam" of blue within the "June Gloom," it appears to be actinoform clouds, a seam in the marine stratocumulus aka "June Gloom" of southern California. Actinoform clouds and marine stratus in general are only marginally stable. Sometimes the cloud deck spontaneously dissolves along a line by drizzling out the moisture. This seam is an unusually long curve that is not identified with a coastline or a weather front. Dennis Chesters/Rob Gutro NASA's Goddard Space Flight Center, Greenbelt, Md. REFERENCES en.wikipedia.org/wiki/Actinoform_cloud en.wikipedia.org/wiki/June_Gloom NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Cloud Forcing and the Earth's Radiation Budget: New Ideas and New Observations

NASA Technical Reports Server (NTRS)

Barkstrom, Bruce R.

1997-01-01

1. NEW PERSPECTIVES ON CLOUD-RADIATIVE FORCING. When the Earth Radiation Budget Experiment (ERBE) produced the first measurements of cloud-radiative forcing, the climate community interpreted the results from a context in which the atmosphere was a single column, strongly coupled to the Earth's surface. 2. NEW PERSPECTIVES ON CLOUD-RADIATION OBSERVATIONS. The climate community is also on the verge of adding a new dimension to its observational capability. In classic thinking about atmospheric circulation and climate, surface pressure was a readily available quantity. As meteorology developed, it was possible to develop quantitative predictions of future weather by bringing together a network of surface pressure observations and then of profiles of temperature and humidity obtained from balloons. 3. ON COMBINING OBSERVATIONS AND THE - ORY. With this new capability, it is natural to seek recognizable features in the observations we make of the Earth. There are techniques we can use to group the remotely sensed data in the individual footprints into objects that we can track. We will present one such image-processing application to radiation budget data, showing how we can interpret the radiation budget data in terms of cloud systems that are organized into systematic patterns of behavior - an ecosystem-like view of cloud behavior.

Antarctica Cloud Cover for October 2003 from GLAS Satellite Lidar Profiling

NASA Technical Reports Server (NTRS)

Spinhirne, J. D.; Palm, S. P.; Hart, W. D.

2005-01-01

Seeing clouds in polar regions has been a problem for the imagers used on satellites. Both clouds and snow and ice are white, which makes clouds over snow hard to see. And for thermal infrared imaging both the surface and the clouds cold. The Geoscience Laser Altimeter System (GLAS) launched in 2003 gives an entirely new way to see clouds from space. Pulses of laser light scatter from clouds giving a signal that is separated in time from the signal from the surface. The scattering from clouds is thus a sensitive and direct measure of the presence and height of clouds. The GLAS instrument orbits over Antarctica 16 times a day. All of the cloud observations for October 2003 were summarized and compared to the results from the MODIS imager for the same month. There are two basic cloud types that are observed, low stratus with tops below 3 km and high cirrus form clouds with cloud top altitude and thickness tending at 12 km and 1.3 km respectively. The average cloud cover varies from over 93 % for ocean and coastal regions to an average of 40% over the East Antarctic plateau and 60-90% over West Antarctica. When the GLAS monthly average cloud fractions are compared to the MODIS cloud fraction data product, differences in the amount of cloud cover are as much as 40% over the continent. The results will be used to improve the way clouds are detected from the imager observations. These measurements give a much improved understanding of distribution of clouds over Antarctica and may show how they are changing as a result of global warming.

Aerosol patterns and aerosol-cloud-interactions off the West African Coast based on the A-train formation

NASA Astrophysics Data System (ADS)

Fuchs, Julia; Bendix, Jörg; Cermak, Jan

2013-04-01

In this study, spatial and temporal aerosol patterns off the Western African coast are characterized and related to cloud properties, based on satellite data Atmospheric aerosols play a key role in atmospheric processes and influence our environmental system in a complex way. Their identification, characterization, transport patterns as well as their interactions with clouds pose major challenges. Especially the last aspect reveals major uncertainties in terms of the Earth's radiation budget as reported in the IPCC's Fourth Assessment Report (IPCC, 2007). Western and Southern Africa are dominated by two well-known source types of atmospheric aerosols. First, the Saharan Desert is the world's largest aeolian dust emitting source region. Second, biomass burning aerosol is commonly transported off-shore further south (Kaufman et al., 2005). Both aerosol types influence Earth's climate in different manners and can be detected by the MODIS (MODerate resolution Imaging Spectrometer) sensor onboard the EOS platforms as they propagate to the Central and Southern Atlantic. The motivation of this study was to reveal the seasonal pattern of the Saharan dust transport based on an observation period of 11 years and trying to explain the meteorological mechanisms. North African dust plumes are transported along a latitude of 19°N in July and 6°N in January. The seasonally fluctuating intensities adapt to the annual cycle of wind and precipitation regimes. A strong relationship is found between the spatial shift of the Azores High and the Saharan dust load over the middle Atlantic Ocean. Monthly Aerosol Optical Thickness products of Terra MODIS and NCEP-DOE (National Centers for Environmental Predictions) Reanalysis II data are used for this purpose. The relationship between aerosol and cloud droplet parameters is blurred by high sensitivities to aerosol size and composition (Feingold, 2003; McFiggans et al., 2006) as well as meteorological context (Ackerman et al., 2004). Satellite data from the A-train formation, including the Aqua, CloudSat and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) are used to analyze aerosol-cloud-interactions in detail, along with re-analysis data to constrain by meteorological conditions. Information about the vertical and geographical distribution of different aerosol types and cloud parameters will lead to a process-oriented understanding of these issues on a regional scale. Ackerman, A., Kirkpatrick, M., Stevens, D., & Toon, O. (2004). The impact of humidity above stratiform clouds on indirect aerosol climate forcing. Nature, 432(December), 1014-1017. doi:10.1038/nature03137.1. Feingold, G. (2003). First measurements of the Twomey indirect effect using ground-based remote sensors. Geophysical Research Letters, 30(6), 1287. doi:10.1029/2002GL016633 IPCC. (2007). Climate Change 2007: The Physical Science Basis. Contribution of Working group I to the Fourth Assessment Report of the Interfovernmental Panel on climate Change. Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Kaufman, Y. J., Koren, I., Remer, L. A., Tanré, D., Ginoux, P., & Fan, S. (2005). Dust transport and deposition observed from the Terra-Moderate Resolution Imaging Spectroradiometer (MODIS) spacecraft over the Atlantic Ocean. Journal of Geophysical Research, 110(D10), 1-16. doi:10.1029/2003JD004436 McFiggans, G., Artaxo, P., Baltensperger, U., Coe, H., Facchini, M. C., Feingold, G., Fuzzi, S., et al. (2006). The effect of physical and chemical aerosol properties on warm cloud droplet activation. Atmospheric Chemistry and Physics, 6(9), 2593-2649. doi:10.5194/acp-6-2593-2006

Partly Cloudy on Pluto?

NASA Image and Video Library

2016-10-18

Pluto's present, hazy atmosphere is almost entirely free of clouds, though scientists from NASA's New Horizons mission have identified some cloud candidates after examining images taken by the New Horizons Long Range Reconnaissance Imager and Multispectral Visible Imaging Camera, during the spacecraft's July 2015 flight through the Pluto system. All are low-lying, isolated small features -- no broad cloud decks or fields -- and while none of the features can be confirmed with stereo imaging, scientists say they are suggestive of possible, rare condensation clouds. http://photojournal.jpl.nasa.gov/catalog/PIA21127

Cloud Computing for radiologists.

PubMed

Kharat, Amit T; Safvi, Amjad; Thind, Ss; Singh, Amarjit

2012-07-01

Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future.

Cloud Computing for radiologists

PubMed Central

Kharat, Amit T; Safvi, Amjad; Thind, SS; Singh, Amarjit

2012-01-01

Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future. PMID:23599560

OpenID Connect as a security service in cloud-based medical imaging systems.

PubMed

Ma, Weina; Sartipi, Kamran; Sharghigoorabi, Hassan; Koff, David; Bak, Peter

2016-04-01

The evolution of cloud computing is driving the next generation of medical imaging systems. However, privacy and security concerns have been consistently regarded as the major obstacles for adoption of cloud computing by healthcare domains. OpenID Connect, combining OpenID and OAuth together, is an emerging representational state transfer-based federated identity solution. It is one of the most adopted open standards to potentially become the de facto standard for securing cloud computing and mobile applications, which is also regarded as "Kerberos of cloud." We introduce OpenID Connect as an authentication and authorization service in cloud-based diagnostic imaging (DI) systems, and propose enhancements that allow for incorporating this technology within distributed enterprise environments. The objective of this study is to offer solutions for secure sharing of medical images among diagnostic imaging repository (DI-r) and heterogeneous picture archiving and communication systems (PACS) as well as Web-based and mobile clients in the cloud ecosystem. The main objective is to use OpenID Connect open-source single sign-on and authorization service and in a user-centric manner, while deploying DI-r and PACS to private or community clouds should provide equivalent security levels to traditional computing model.

HoloGondel: in situ cloud observations on a cable car in the Swiss Alps using a holographic imager

NASA Astrophysics Data System (ADS)

Beck, Alexander; Henneberger, Jan; Schöpfer, Sarah; Fugal, Jacob; Lohmann, Ulrike

2017-02-01

In situ observations of cloud properties in complex alpine terrain where research aircraft cannot sample are commonly conducted at mountain-top research stations and limited to single-point measurements. The HoloGondel platform overcomes this limitation by using a cable car to obtain vertical profiles of the microphysical and meteorological cloud parameters. The main component of the HoloGondel platform is the HOLographic Imager for Microscopic Objects (HOLIMO 3G), which uses digital in-line holography to image cloud particles. Based on two-dimensional images the microphysical cloud parameters for the size range from small cloud particles to large precipitation particles are obtained for the liquid and ice phase. The low traveling velocity of a cable car on the order of 10 m s-1 allows measurements with high spatial resolution; however, at the same time it leads to an unstable air speed towards the HoloGondel platform. Holographic cloud imagers, which have a sample volume that is independent of the air speed, are therefore well suited for measurements on a cable car. Example measurements of the vertical profiles observed in a liquid cloud and a mixed-phase cloud at the Eggishorn in the Swiss Alps in the winters 2015 and 2016 are presented. The HoloGondel platform reliably observes cloud droplets larger than 6.5 µm, partitions between cloud droplets and ice crystals for a size larger than 25 µm and obtains a statistically significantly size distribution for every 5 m in vertical ascent.

Insights into the diurnal cycle of global Earth outgoing radiation using a numerical weather prediction model

NASA Astrophysics Data System (ADS)

Gristey, Jake J.; Chiu, J. Christine; Gurney, Robert J.; Morcrette, Cyril J.; Hill, Peter G.; Russell, Jacqueline E.; Brindley, Helen E.

2018-04-01

A globally complete, high temporal resolution and multiple-variable approach is employed to analyse the diurnal cycle of Earth's outgoing energy flows. This is made possible via the use of Met Office model output for September 2010 that is assessed alongside regional satellite observations throughout. Principal component analysis applied to the long-wave component of modelled outgoing radiation reveals dominant diurnal patterns related to land surface heating and convective cloud development, respectively explaining 68.5 and 16.0 % of the variance at the global scale. The total variance explained by these first two patterns is markedly less than previous regional estimates from observations, and this analysis suggests that around half of the difference relates to the lack of global coverage in the observations. The first pattern is strongly and simultaneously coupled to the land surface temperature diurnal variations. The second pattern is strongly coupled to the cloud water content and height diurnal variations, but lags the cloud variations by several hours. We suggest that the mechanism controlling the delay is a moistening of the upper troposphere due to the evaporation of anvil cloud. The short-wave component of modelled outgoing radiation, analysed in terms of albedo, exhibits a very dominant pattern explaining 88.4 % of the variance that is related to the angle of incoming solar radiation, and a second pattern explaining 6.7 % of the variance that is related to compensating effects from convective cloud development and marine stratocumulus cloud dissipation. Similar patterns are found in regional satellite observations, but with slightly different timings due to known model biases. The first pattern is controlled by changes in surface and cloud albedo, and Rayleigh and aerosol scattering. The second pattern is strongly coupled to the diurnal variations in both cloud water content and height in convective regions but only cloud water content in marine stratocumulus regions, with substantially shorter lag times compared with the long-wave counterpart. This indicates that the short-wave radiation response to diurnal cloud development and dissipation is more rapid, which is found to be robust in the regional satellite observations. These global, diurnal radiation patterns and their coupling with other geophysical variables demonstrate the process-level understanding that can be gained using this approach and highlight a need for global, diurnal observing systems for Earth outgoing radiation in the future.

Smoke over Hudson Bay

NASA Image and Video Library

2017-12-08

A vigorous summer fire season continued through July, 2013 as many large wildfires continued to burn in the forests of northern Canada. The high fire activity not only laid waste to thousands of hectares of boreal forest, but sent thick smoke billowing high into the atmosphere, where it was carried far across the Atlantic Ocean. On July 30, the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA’s Aqua satellite captured this true-color image of a river of smoke spreading south across the Hudson Bay. The blue background is formed by the waters of Hudson Bay. In the southeast the green, forest-covered land of Quebec province peeks from under a large cloud bank. Another large bank of white cloud covers the water in the southwest, and a smaller cloud bank covers the territory of Nunavut in the northwest. A bit of Baffin Island can be seen near the top center of the image. Looking closely at the image, it appears that the gray smoke mixes with whiter cloud in the south, suggesting they may be at the same level in the atmosphere. In the northeast corner of the image, a ribbon of smoke appears to blow over a bank of popcorn clouds as well as over a few lower-lying clouds, causing some of the clouds to appear gray beneath the smoky veil. Where cloud meets smoke in the northeast, however, the line of the cloud bank remains sharp, while the smoke appears to continue traveling under the edge. Although these interpretations are somewhat subjective in this true-color image, the false-color image of the same scene (not shown here) lends strength to the interpretation. Data from other NASA instruments, designed to measure cloud height and characteristics, agree that clouds vary in height, and that smoke mingles with cloud in the south. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

User Observed Estimates of Cloud Fraction for Modifying a Cloud-free UV Index for Use in an Educational Smart-phone Application on Erythema

NASA Astrophysics Data System (ADS)

Lantz, K. O.; Long, C. S.; Buller, D.; Berwick, M.; Buller, M.; Kane, I.; Shane, J.

2012-12-01

The UV Index (UVI) is a measure of the skin-damaging UV radiation levels at the Earth's surface. Clouds, haze, air pollution, total ozone, surface elevation, and ground reflectivity affect the levels of UV radiation reaching the ground. The global UV Index was developed as a simple tool to educate the public for taking precautions when exposed to UV radiation to avoid sun-burning, which has been linked to the development of skin cancer. The purpose of this study was to validate an algorithm to modify a cloud-free UV Index forecast for cloud conditions as observed by adults in real-time. The cloud attenuation algorithm is used in a smart-phone application to modify a clear-sky UV Index forecast. In the United States, the Climate Prediction Center of the National Oceanic and Atmospheric Administration's (NOAA) issues a daily UV Index Forecast. The NOAA UV Index is an hourly forecast for a 0.5 x 0.5 degree area and thus has a degree of uncertainty. Cloud cover varies temporally and spatially over short times and distances as weather conditions change and can have a large impact on the UV radiation. The smart-phone application uses the cloud-based UV Index forecast as the default but allows the user to modify a cloud-free UV Index forecast when the predicted sky conditions do not match observed conditions. Eighty four (n=84) adults were recruited to participate in the study through advertisements posted online and in a university e-newsletter. Adults were screened for eligibility (i.e., 18 or older, capable to traveling to test site, had a smart phone with a data plan to access online observation form). A sky observation measure was created to assess cloud fraction. The adult volunteers selected from among four photographs the image that best matched the cloud conditions they observed. Images depicted no clouds (clear sky), thin high clouds, partly cloudy sky, and thick clouds (sky completely overcast). When thin high clouds or partly cloudy images were selected, adults estimated the percentage of the sky covered by clouds. Cloud fraction was calculated by assigning 0% if the clear-sky image was selected, 100% if the overcast thick cloud image was selected, and 10% to 90% as indicated by adults, if high thin clouds or partly cloudy images were selected. The observed cloud fraction from the adult volunteers was compared to the cloud fraction determined by a Total Sky Imager. A cloud modification factor based on the observed cloud fraction was applied to the cloud-free UV Index forecast. This result was compared to the NOAA cloudy sky UV Index forecast and to the concurrent UV Index measurements from three broadband UV radiometers and a Brewer spectrophotometer calibrated using NIST traceable standards.

Smoke From Canadian Wildfires Trapped in Clouds

NASA Image and Video Library

2017-12-08

NASA's Aqua satellite captured this image of the clouds over Canada. Entwined within the clouds is the smoke billowing up from the wildfires that are currently burning across a large expanse of the country. The smoke has become entrained within the clouds causing it to twist within the circular motion of the clouds and wind. This image was taken by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the Aqua satellite on May 9, 2016. Image Credit: NASA image courtesy Jeff Schmaltz LANCE/EOSDIS MODIS Rapid Response Team, GSFC NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Cloud Retrieval Information Content Studies with the Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Ocean Color Imager (OCI)

NASA Astrophysics Data System (ADS)

Coddington, Odele; Platnick, Steven; Pilewskie, Peter; Schmidt, Sebastian

2016-04-01

The NASA Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Science Definition Team (SDT) report released in 2012 defined imager stability requirements for the Ocean Color Instrument (OCI) at the sub-percent level. While the instrument suite and measurement requirements are currently being determined, the PACE SDT report provided details on imager options and spectral specifications. The options for a threshold instrument included a hyperspectral imager from 350-800 nm, two near-infrared (NIR) channels, and three short wave infrared (SWIR) channels at 1240, 1640, and 2130 nm. Other instrument options include a variation of the threshold instrument with 3 additional spectral channels at 940, 1378, and 2250 nm and the inclusion of a spectral polarimeter. In this work, we present cloud retrieval information content studies of optical thickness, droplet effective radius, and thermodynamic phase to quantify the potential for continuing the low cloud climate data record established by the MOderate Resolution and Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) missions with the PACE OCI instrument (i.e., non-polarized cloud reflectances and in the absence of midwave and longwave infrared channels). The information content analysis is performed using the GEneralized Nonlinear Retrieval Analysis (GENRA) methodology and the Collection 6 simulated cloud reflectance data for the common MODIS/VIIRS algorithm (MODAWG) for Cloud Mask, Cloud-Top, and Optical Properties. We show that using both channels near 2 microns improves the probability of cloud phase discrimination with shortwave-only cloud reflectance retrievals. Ongoing work will extend the information content analysis, currently performed for dark ocean surfaces, to different land surface types.

Time scales of pattern evolution from cross-spectrum analysis of advanced very high resolution radiometer and coastal zone color scanner imagery

NASA Technical Reports Server (NTRS)

Denman, Kenneth L.; Abbott, Mark R.

1994-01-01

We have selected square subareas (110 km on a side) from coastal zone color scanner (CZCS) and advanced very high resolution radiometer (AVHRR) images for 1981 in the California Current region off northern California for which we could identify sequences of cloud-free data over periods of days to weeks. We applied a two-dimensional fast Fourier transformation to images after median filtering, (x, y) plane removal, and cosine tapering. We formed autospectra and coherence spectra as functions of a scalar wavenumber. Coherence estimates between pairs of images were plotted against time separation between images for several wide wavenumber bands to provide a temporal lagged coherence function. The temporal rate of loss of correlation (decorrelation time scale) in surface patterns provides a measure of the rate of pattern change or evolution as a function of spatial dimension. We found that patterns evolved (or lost correlation) approximately twice as rapidly in upwelling jets as in the 'quieter' regions between jets. The rapid evolution of pigment patterns (lifetime of about 1 week or less for scales of 50-100 km) ought to hinder biomass transfer to zooplankton predators compared with phytoplankton patches that persist for longer times. We found no significant differences between the statistics of CZCS and AVHRR images (spectral shape or rate of decorrelation). In addition, in two of the three areas studied, the peak correlation between AVHRR and CZCS images from the same area occurred at zero lag, indicating that the patterns evolved simutaneously. In the third area, maximum coherence between thermal and pigment patterns occurred when pigment images lagged thermal images by 1-2 days, mirroring the expected lag of high pigment behind low temperatures (and high nutrients) in recently upwelled water. We conclude that in dynamic areas such as coastal upwelling systems, the phytoplankton cells (identified by pigment color patterns) behave largely as passive scalars at the mesoscale and that growth, death, and sinking of phytoplankton collectively play at most a mariginal role in determining the spectral statistics of the pigment patterns.

17 Years of Cloud Heights from Terra, and Beyond

NASA Astrophysics Data System (ADS)

Davies, R.

2017-12-01

The effective cloud height, H, is the integral of observed cloud-top heights, weighted by their frequency of occurrence. Here we look at changes in the effective cloud height, H', as measured by the Multiangle Imaging Spectroradiometer (MISR) on the first Earth Observing System platform, Terra. Terra was launched in December 1999, and now has over 17 years of consistently measured climate records. Globally, HG' has an important influence on Earth's climate, whereas regionally, HR' is a useful measure of low frequency changes in circulation patterns. MISR has a sampling error in the annual mean HG' of ≈11 m, allowing fairly small interannual variations to be detected. This paper extends the previous 15-year summary that showed significant differences in the long term mean hemispheric cloud height changes. Also of interest are the correlations in tropical cloud height changes and related teleconnections. The largest ephemeral values in the annual HR' [over 1.5 km] are noted over the Central Pacific and the Maritime Continent. These changes are strongly anticorrelated with each other, being directly related to changes in ENSO. They are also correlated with the largest ephemeral changes in HG'. Around the equator, we find at least four distinct centres of similar fluctuations in cloud height. This paper examines the relative time dependence of these regional height changes, separately for La Niña and El Niño events, and stresses the value of extending the time series of uniformly measured cloud heights from space beyond EOS-Terra.

Thunderheads on Jupiter

NASA Image and Video Library

1997-09-08

Scientists have spotted what appear to be thunderheads on Jupiter bright white cumulus clouds similar to those that bring thunderstorms on Earth - at the outer edges of Jupiter's Great Red Spot. Images from NASA's Galileo spacecraft now in orbit around Jupiter are providing new evidence that thunderstorms may be an important source of energy for Jupiter's winds that blow at more than 500 kilometers per hour (about 300 miles per hour). The photos were taken by Galileo's solid state imager camera on June 26, 1996 at a range of about 1.4 million kilometers (about 860,000 miles). The image at top is a mosaic of multiple images taken through near-infrared filters. False coloring in the image reveals cloud-top heights. High, thick clouds are white and high, thin clouds are pink. Low-altitude clouds are blue. The two black-and-white images at bottom are enlargements of the boxed area; the one on the right was taken 70 minutes after the image on the left. The arrows show where clouds have formed or dissipated in the short time between the images. The smallest clouds are tens of kilometers across. On Earth, moist convection in thunderstorms is a pathway through which solar energy, deposited at the surface, is transported and delivered to the atmosphere. Scientists at the California Institute of Technology analyzing data from Galileo believe that water, the most likely candidate for what composes these clouds on Jupiter, may be more abundant at the site seen here than at the Galileo Probe entry site, which was found to be unexpectedly dry. http://photojournal.jpl.nasa.gov/catalog/PIA00506

Vector velocity profiles of the solar wind within expanding magnetic clouds at 1 AU: Some surprises

NASA Astrophysics Data System (ADS)

Wu, C.; Lepping, R. P.; Berdichevsky, D.; Ferguson, T.; Lazarus, A. J.

2002-12-01

We investigated the average vector velocity profile of 36 carefully chosen WIND interplanetary magnetic clouds occurring over about a 7 year period since spacecraft launch, to see if a differential pattern of solar wind flow exists. Particular cases were chosen of clouds whose axes were generally within 45 degrees of the ecliptic plane and of relatively well determined characteristics obtained from cloud-parameter (cylindrically symmetric force free) fitting. This study was motivated by the desire to understand the manner in which magnetic clouds expand, a well know phenomenon revealed by most cloud speed-profiles at 1 AU. One unexpected and major result was that, even though cloud expansion was confirmed, it was primarily along the Xgse axis; i.e., neither the Ygse or Zgse velocity components reveal any noteworthy pattern. After splitting the full set of clouds into a north-passing set (spacecraft passing above the cloud, where Nn = 21) and south-passing set (Ns = 15), to study the plasma expansion of the clouds with respect to the position of the observer, it was seen that the Xgse component of velocity differs for these two sets in a rather uniform and measurable way for most of the average cloud's extent. This does not appear to be the case for the Ygse or Zgse velocity components where little measurable differences exists, and clearly no pattern, across the average cloud between the north and south positions. It is not clear why such a remarkably non-axisymmetric plasma flow pattern within the "average magnetic cloud" at 1 AU should exist. The study continues from the perspective of magnetic cloud coordinate representation. ~ ~ ~

HST and ground-based observations of bright storms on Uranus during 2014-2015.

NASA Astrophysics Data System (ADS)

Sayanagi, K. M.; Sromovsky, L. A.; Fry, P. M.; De Pater, I.; Hammel, H. B.; Rages, K. A.; Baranec, C.; Delcroix, M.; Wesley, A.; Hueso, R.; Sanchez-Lavega, A.; Simon, A. A.; Wong, M. H.; Orton, G. S.; Irwin, P. G.

2015-12-01

We report the temporal evolution of bright, long-lived cloud features on Uranus. We observed and tracked the features between August 2014 and January 2015 with the Hubble Space Telescope, the Keck 2 10-m telescope, VLT, Gran Telescopio Canarias, Gemini, William Herschel Telescope, Robo-AO, Pic du Midi 1-m telescope, and multiple smaller telescopes operated by amateur astronomers. Surprisingly bright features were first revealed in the Keck adaptive-optics images in August; this initial set of observations motivated follow-up observations around the world. One of the storms (identified as "Feature F" in Sromovsky et al. 2015, and Feature 2 in de Pater et al. 2015), which was the deepest in that dataset, was bright enough that it was detected by multiple amateur observers, permitting us to trigger a Hubble Target of Opportunity (ToO) observation on October 14th, 2014. A complex of features at this latitude was also observed by Hubble as part of the Outer Planet Atmospheres Legacy (OPAL) program on November 8-9, 2014. We will present the temporal evolution of the cloud activities from August 2014 through January 2015, and analyze the vertical structure of the cloud features in the Hubble datasets. The Hubble images used in our study were collected with support of HST grants GO13712 to KMS and GO13937 to AAS. Sromovsky et al. 2015, "High S/N Keck and Gemini AO imaging of Uranus during 2012-2014: New cloud patterns, increasing activity, and improved wind measurements." Icarus 258, 192-223. de Pater et al. 2014, "Record-breaking storm activity on Uranus in 2014." Icarus 252, 121-128

Investigation of Jupiter's Equatorial Hotspots and Plumes Using Cassini ISS Observations

NASA Technical Reports Server (NTRS)

Choi, David S.; Showman, A. P.; Vasavada, A. R.; Simon-Miller, A. A.

2012-01-01

We present updated analysis of Jupiter's equatorial meteorology from Cassini observations. For two months preceding the spacecraft's closest approach, the ISS onboard regularly imaged the atmosphere. We created time-lapse movies from this period in order to analyze the dynamics of equatorial 5-micron hot spots and their interactions with adjacent latitudes. Hot spots are quasi-stable, rectangular dark areas on visible-wavelength images, with defined eastern edges that sharply contrast with surrounding clouds, but a diffuse western edge serving as a nebulous boundary with adjacent equatorial plumes. Hot spots exhibit significant variations in size and shape over timescales of days and weeks. Some of these changes correspond with passing vortex systems from adjacent latitudes interacting with hot spots. Strong anticyclonic gyres present to the south and southeast of the dark areas appear to circulate into hot spots. Impressive, bright white plumes occupy spaces in between hot spots. Compact cirrus-iike 'scooter' clouds flow rapidly through the plumes before disappearing within the dark areas. This raises the possibility that the plumes and fast-moving clouds are at higher altitudes, because their speed does not match previously published zonal wind profiles. Most profiles represent the drift speed of the hot spots at their latitude from pattern matching of the entire longitudinal image strip. If a downward branch of an equatorially-trapped Rossby waves controls the overall appearance of hot spots, however, the westward phase velocity of the wave leads to underestimates of the true jet stream speed. Instead, our expanded data set demonstrating the rapid flow of these scooter clouds may be more illustrative of the actual jet stream speed at these latitudes. This research was supported by a NASA JDAP grant and the NASA Postdoctoral Program.

A comparison of performance of automatic cloud coverage assessment algorithm for Formosat-2 image using clustering-based and spatial thresholding methods

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2012-11-01

Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.

Jupiter's Colorful Cloud Belts

NASA Image and Video Library

2018-01-12

Colorful swirling cloud belts dominate Jupiter's southern hemisphere in this image captured by NASA's Juno spacecraft. Jupiter appears in this color-enhanced image as a tapestry of vibrant cloud bands and storms. The dark region in the far left is called the South Temperate Belt. Intersecting the belt is a ghost-like feature of slithering white clouds. This is the largest feature in Jupiter's low latitudes that's a cyclone (rotating with clockwise motion). This image was taken on Dec. 16, 2017 at 10:12 PST (1:12 p.m. EST), as Juno performed its tenth close flyby of Jupiter. At the time the image was taken, the spacecraft was about 8,453 miles (13,604 kilometers) from the tops of the clouds of the planet at a latitude of 27.9 degrees south. The spatial scale in this image is 5.6 miles/pixel (9.1 kilometers/pixel). Citizen scientist Kevin M. Gill processed this image using data from the JunoCam imager. https://photojournal.jpl.nasa.gov/catalog/PIA21974

Cloud chamber experiments on the origin of ice crystal complexity in cirrus clouds

NASA Astrophysics Data System (ADS)

Schnaiter, Martin; Järvinen, Emma; Vochezer, Paul; Abdelmonem, Ahmed; Wagner, Robert; Jourdan, Olivier; Mioche, Guillaume; Shcherbakov, Valery N.; Schmitt, Carl G.; Tricoli, Ugo; Ulanowski, Zbigniew; Heymsfield, Andrew J.

2016-04-01

This study reports on the origin of small-scale ice crystal complexity and its influence on the angular light scattering properties of cirrus clouds. Cloud simulation experiments were conducted at the AIDA (Aerosol Interactions and Dynamics in the Atmosphere) cloud chamber of the Karlsruhe Institute of Technology (KIT). A new experimental procedure was applied to grow and sublimate ice particles at defined super- and subsaturated ice conditions and for temperatures in the -40 to -60 °C range. The experiments were performed for ice clouds generated via homogeneous and heterogeneous initial nucleation. Small-scale ice crystal complexity was deduced from measurements of spatially resolved single particle light scattering patterns by the latest version of the Small Ice Detector (SID-3). It was found that a high crystal complexity dominates the microphysics of the simulated clouds and the degree of this complexity is dependent on the available water vapor during the crystal growth. Indications were found that the small-scale crystal complexity is influenced by unfrozen H2SO4 / H2O residuals in the case of homogeneous initial ice nucleation. Angular light scattering functions of the simulated ice clouds were measured by the two currently available airborne polar nephelometers: the polar nephelometer (PN) probe of Laboratoire de Métérologie et Physique (LaMP) and the Particle Habit Imaging and Polar Scattering (PHIPS-HALO) probe of KIT. The measured scattering functions are featureless and flat in the side and backward scattering directions. It was found that these functions have a rather low sensitivity to the small-scale crystal complexity for ice clouds that were grown under typical atmospheric conditions. These results have implications for the microphysical properties of cirrus clouds and for the radiative transfer through these clouds.

On the Influence of Air Mass Origin on Low-Cloud Properties in the Southeast Atlantic

NASA Astrophysics Data System (ADS)

Fuchs, Julia; Cermak, Jan; Andersen, Hendrik; Hollmann, Rainer; Schwarz, Katharina

2017-10-01

This study investigates the impact of air mass origin and dynamics on cloud property changes in the Southeast Atlantic (SEA) during the biomass burning season. The understanding of clouds and their determinants at different scales is important for constraining the Earth's radiative budget and thus prominent in climate system research. In this study, the thermodynamically stable SEA stratocumulus cover is observed not only as the result of local environmental conditions but also as connected to large-scale meteorology by the often neglected but important role of spatial origins of air masses entering this region. In order to assess to what extent cloud properties are impacted by aerosol concentration, air mass history, and meteorology, a Hybrid Single-Particle Lagrangian Integrated Trajectory cluster analysis is conducted linking satellite observations of cloud properties (Spinning-Enhanced Visible and Infrared Imager), information on aerosol species (Monitoring Atmospheric Composition and Climate), and meteorological context (ERA-Interim reanalysis) to air mass clusters. It is found that a characteristic pattern of air mass origins connected to distinct synoptical conditions leads to marked cloud property changes in the southern part of the study area. Long-distance air masses are related to midlatitude weather disturbances that affect the cloud microphysics, especially in the southwestern subdomain of the study area. Changes in cloud effective radius are consistent with a boundary layer deepening and changes in lower tropospheric stability (LTS). In the southeastern subdomain cloud cover is controlled by a generally higher LTS, while air mass origin plays a minor role. This study leads to a better understanding of the dynamical drivers behind observed stratocumulus cloud properties in the SEA and frames potentially interesting conditions for aerosol-cloud interactions.

Probing Storm Activity on Jupiter

NASA Technical Reports Server (NTRS)

2007-01-01

Scientists assume Jupiter's clouds are composed primarily of ammonia, but only about 1% of the cloud area displays the characteristic spectral fingerprint of ammonia. This composite of infrared images taken by the New Horizons Linear Etalon Infrared Spectral Imager (LEISA) captures several eruptions of this relatively rare breed of ammonia cloud and follows the evolution of the clouds over two Jovian days. (One day on Jupiter is approximately 10 hours, which is how long it takes Jupiter to make one complete rotation about its axis.)

The New Horizons spacecraft was still closing in on the giant planet when it made these observations: Jupiter was 3.4 million kilometers (2.1 million miles) from the New Horizons spacecraft for the LEISA image taken at 19:35 Universal Time on February 26, 2007, and the distance decreased to 2.5 million kilometers (1.6 million miles) for the last image shown. LEISA's spatial resolution scale varied from approximately 210 kilometers (130 miles) for the first image to 160 kilometers (100 miles) for the last one.

New Horizons scientists originally targeted the region slightly northwest (up and to the left) of the Great Red Spot to search for these special ammonia clouds because that's where they were most easily seen during infrared spectral observations made by the Galileo spacecraft. But unlike the churning, turbulent cloud structures seen near the Great Red Spot during the Galileo era, this region has been quieting down during the past several months and was unusually tranquil when New Horizons passed by. Nevertheless, LEISA managed to find other regions of fresh, upwelling ammonia clouds, and the temporal evolution of one such region is displayed in this figure. In the first image, a fresh ammonia cloud (the blue region) sprouts from between white clouds and a dark elongated region. This blue cloud subsequently stretches along the white-dark border in the next two images.

These fresh ammonia clouds trace the strong upwelling of gases from the largely hidden depths of Jupiter to higher altitudes. Presumably, water is also being dragged up from below, and the subsequent condensation of that water, which is far more abundant than ammonia in Jupiter's atmosphere, into cloud droplets energizes the lower troposphere.

LEISA produces images at infrared wavelengths, which is heat radiation that cannot be sensed by the human eye. These 'false color' images were produced by putting images of Jupiter at wavelengths of 1.99 micrometers, 1.94 micrometers and 2.04 micrometers into the red, green and blue channels, respectively, of the image display. Ammonia has an absorption feature at 1.99 microns, and when the colors are combined in this way the fresh ammonia clouds take on a bluish hue.

Jovian Tempest

NASA Image and Video Library

2017-11-16

This color-enhanced image of a massive, raging storm in Jupiter's northern hemisphere was captured by NASA's Juno spacecraft during its ninth close flyby of the gas giant planet. The image was taken on Oct. 24, 2017 at 10:32 a.m. PDT (1:32 p.m. EDT). At the time the image was taken, the spacecraft was about 6,281 miles (10,108 kilometers) from the tops of the clouds of Jupiter at a latitude of 41.84 degrees. The spatial scale in this image is 4.2 miles/pixel (6.7 kilometers/pixel). The storm is rotating counter-clockwise with a wide range of cloud altitudes. The darker clouds are expected to be deeper in the atmosphere than the brightest clouds. Within some of the bright "arms" of this storm, smaller clouds and banks of clouds can be seen, some of which are casting shadows to the right side of this picture (sunlight is coming from the left). The bright clouds and their shadows range from approximately 4 to 8 miles (7 to 12 kilometers) in both widths and lengths. These appear similar to the small clouds in other bright regions Juno has detected and are expected to be updrafts of ammonia ice crystals possibly mixed with water ice. Citizen scientists Gerald Eichstädt and Seán Doran processed this image using data from the JunoCam imager. https://photojournal.jpl.nasa.gov/catalog/PIA21971

Jupiter's Multi-level Clouds

NASA Technical Reports Server (NTRS)

1997-01-01

Clouds and hazes at various altitudes within the dynamic Jovian atmosphere are revealed by multi-color imaging taken by the Near-Infrared Mapping Spectrometer (NIMS) onboard the Galileo spacecraft. These images were taken during the second orbit (G2) on September 5, 1996 from an early-morning vantage point 2.1 million kilometers (1.3 million miles) above Jupiter. They show the planet's appearance as viewed at various near-infrared wavelengths, with distinct differences due primarily to variations in the altitudes and opacities of the cloud systems. The top left and right images, taken at 1.61 microns and 2.73 microns respectively, show relatively clear views of the deep atmosphere, with clouds down to a level about three times the atmospheric pressure at the Earth's surface.

By contrast, the middle image in top row, taken at 2.17 microns, shows only the highest altitude clouds and hazes. This wavelength is severely affected by the absorption of light by hydrogen gas, the main constituent of Jupiter's atmosphere. Therefore, only the Great Red Spot, the highest equatorial clouds, a small feature at mid-northern latitudes, and thin, high photochemical polar hazes can be seen. In the lower left image, at 3.01 microns, deeper clouds can be seen dimly against gaseous ammonia and methane absorption. In the lower middle image, at 4.99 microns, the light observed is the planet's own indigenous heat from the deep, warm atmosphere.

The false color image (lower right) succinctly shows various cloud and haze levels seen in the Jovian atmosphere. This image indicates the temperature and altitude at which the light being observed is produced. Thermally-rich red areas denote high temperatures from photons in the deep atmosphere leaking through minimal cloud cover; green denotes cool temperatures of the tropospheric clouds; blue denotes cold of the upper troposphere and lower stratosphere. The polar regions appear purplish, because small-particle hazes allow leakage and reflectivity, while yellowish regions at temperate latitudes may indicate tropospheric clouds with small particles which also allow leakage. A mix of high and low-altitude aerosols causes the aqua appearance of the Great Red Spot and equatorial region.

The Jet Propulsion Laboratory manages the Galileo mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web Galileo mission home page at http://galileo.jpl.nasa.gov.

High-Resolution Surface Reconstruction from Imagery for Close Range Cultural Heritage Applications

NASA Astrophysics Data System (ADS)

Wenzel, K.; Abdel-Wahab, M.; Cefalu, A.; Fritsch, D.

2012-07-01

The recording of high resolution point clouds with sub-mm resolution is a demanding and cost intensive task, especially with current equipment like handheld laser scanners. We present an image based approached, where techniques of image matching and dense surface reconstruction are combined with a compact and affordable rig of off-the-shelf industry cameras. Such cameras provide high spatial resolution with low radiometric noise, which enables a one-shot solution and thus an efficient data acquisition while satisfying high accuracy requirements. However, the largest drawback of image based solutions is often the acquisition of surfaces with low texture where the image matching process might fail. Thus, an additional structured light projector is employed, represented here by the pseudo-random pattern projector of the Microsoft Kinect. Its strong infrared-laser projects speckles of different sizes. By using dense image matching techniques on the acquired images, a 3D point can be derived for almost each pixel. The use of multiple cameras enables the acquisition of a high resolution point cloud with high accuracy for each shot. For the proposed system up to 3.5 Mio. 3D points with sub-mm accuracy can be derived per shot. The registration of multiple shots is performed by Structure and Motion reconstruction techniques, where feature points are used to derive the camera positions and rotations automatically without initial information.

Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

NASA Astrophysics Data System (ADS)

Champion, Nicolas

2016-06-01

Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pléiades-HR images and our first experiments show the feasibility to automate the detection of shadows and clouds in satellite image sequences.

Image phase shift invariance based cloud motion displacement vector calculation method for ultra-short-term solar PV power forecasting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Fei; Zhen, Zhao; Liu, Chun

Irradiance received on the earth's surface is the main factor that affects the output power of solar PV plants, and is chiefly determined by the cloud distribution seen in a ground-based sky image at the corresponding moment in time. It is the foundation for those linear extrapolation-based ultra-short-term solar PV power forecasting approaches to obtain the cloud distribution in future sky images from the accurate calculation of cloud motion displacement vectors (CMDVs) by using historical sky images. Theoretically, the CMDV can be obtained from the coordinate of the peak pulse calculated from a Fourier phase correlation theory (FPCT) method throughmore » the frequency domain information of sky images. The peak pulse is significant and unique only when the cloud deformation between two consecutive sky images is slight enough, which is likely possible for a very short time interval (such as 1?min or shorter) with common changes in the speed of cloud. Sometimes, there will be more than one pulse with similar values when the deformation of the clouds between two consecutive sky images is comparatively obvious under fast changing cloud speeds. This would probably lead to significant errors if the CMDVs were still only obtained from the single coordinate of the peak value pulse. However, the deformation estimation of clouds between two images and its influence on FPCT-based CMDV calculations are terrifically complex and difficult because the motion of clouds is complicated to describe and model. Therefore, to improve the accuracy and reliability under these circumstances in a simple manner, an image-phase-shift-invariance (IPSI) based CMDV calculation method using FPCT is proposed for minute time scale solar power forecasting. First, multiple different CMDVs are calculated from the corresponding consecutive images pairs obtained through different synchronous rotation angles compared to the original images by using the FPCT method. Second, the final CMDV is generated from all of the calculated CMDVs through a centroid iteration strategy based on its density and distance distribution. Third, the influence of different rotation angle resolution on the final CMDV is analyzed as a means of parameter estimation. Simulations under various scenarios including both thick and thin clouds conditions indicated that the proposed IPSI-based CMDV calculation method using FPCT is more accurate and reliable than the original FPCT method, optimal flow (OF) method, and particle image velocimetry (PIV) method.« less

Image phase shift invariance based cloud motion displacement vector calculation method for ultra-short-term solar PV power forecasting

DOE PAGES

Wang, Fei; Zhen, Zhao; Liu, Chun; ...

2017-12-18

Irradiance received on the earth's surface is the main factor that affects the output power of solar PV plants, and is chiefly determined by the cloud distribution seen in a ground-based sky image at the corresponding moment in time. It is the foundation for those linear extrapolation-based ultra-short-term solar PV power forecasting approaches to obtain the cloud distribution in future sky images from the accurate calculation of cloud motion displacement vectors (CMDVs) by using historical sky images. Theoretically, the CMDV can be obtained from the coordinate of the peak pulse calculated from a Fourier phase correlation theory (FPCT) method throughmore » the frequency domain information of sky images. The peak pulse is significant and unique only when the cloud deformation between two consecutive sky images is slight enough, which is likely possible for a very short time interval (such as 1?min or shorter) with common changes in the speed of cloud. Sometimes, there will be more than one pulse with similar values when the deformation of the clouds between two consecutive sky images is comparatively obvious under fast changing cloud speeds. This would probably lead to significant errors if the CMDVs were still only obtained from the single coordinate of the peak value pulse. However, the deformation estimation of clouds between two images and its influence on FPCT-based CMDV calculations are terrifically complex and difficult because the motion of clouds is complicated to describe and model. Therefore, to improve the accuracy and reliability under these circumstances in a simple manner, an image-phase-shift-invariance (IPSI) based CMDV calculation method using FPCT is proposed for minute time scale solar power forecasting. First, multiple different CMDVs are calculated from the corresponding consecutive images pairs obtained through different synchronous rotation angles compared to the original images by using the FPCT method. Second, the final CMDV is generated from all of the calculated CMDVs through a centroid iteration strategy based on its density and distance distribution. Third, the influence of different rotation angle resolution on the final CMDV is analyzed as a means of parameter estimation. Simulations under various scenarios including both thick and thin clouds conditions indicated that the proposed IPSI-based CMDV calculation method using FPCT is more accurate and reliable than the original FPCT method, optimal flow (OF) method, and particle image velocimetry (PIV) method.« less

High-dynamic-range imaging for cloud segmentation

NASA Astrophysics Data System (ADS)

Dev, Soumyabrata; Savoy, Florian M.; Lee, Yee Hui; Winkler, Stefan

2018-04-01

Sky-cloud images obtained from ground-based sky cameras are usually captured using a fisheye lens with a wide field of view. However, the sky exhibits a large dynamic range in terms of luminance, more than a conventional camera can capture. It is thus difficult to capture the details of an entire scene with a regular camera in a single shot. In most cases, the circumsolar region is overexposed, and the regions near the horizon are underexposed. This renders cloud segmentation for such images difficult. In this paper, we propose HDRCloudSeg - an effective method for cloud segmentation using high-dynamic-range (HDR) imaging based on multi-exposure fusion. We describe the HDR image generation process and release a new database to the community for benchmarking. Our proposed approach is the first using HDR radiance maps for cloud segmentation and achieves very good results.

A SAR Observation and Numerical Study on Ocean Surface Imprints of Atmospheric Vortex Streets.

PubMed

Li, Xiaofeng; Zheng, Weizhong; Zou, Cheng-Zhi; Pichel, William G

2008-05-21

The sea surface imprints of Atmospheric Vortex Street (AVS) off Aleutian Volcanic Islands, Alaska were observed in two RADARSAT-1 Synthetic Aperture Radar (SAR) images separated by about 11 hours. In both images, three pairs of distinctive vortices shedding in the lee side of two volcanic mountains can be clearly seen. The length and width of the vortex street are about 60-70 km and 20 km, respectively. Although the AVS's in the two SAR images have similar shapes, the structure of vortices within the AVS is highly asymmetrical. The sea surface wind speed is estimated from the SAR images with wind direction input from Navy NOGAPS model. In this paper we present a complete MM5 model simulation of the observed AVS. The surface wind simulated from the MM5 model is in good agreement with SAR-derived wind. The vortex shedding rate calculated from the model run is about 1 hour and 50 minutes. Other basic characteristics of the AVS including propagation speed of the vortex, Strouhal and Reynolds numbers favorable for AVS generation are also derived. The wind associated with AVS modifies the cloud structure in the marine atmospheric boundary layer. The AVS cloud pattern is also observed on a MODIS visible band image taken between the two RADARSAT SAR images. An ENVISAT advance SAR image taken 4 hours after the second RADARSAT SAR image shows that the AVS has almost vanished.

Crew Earth Observations (CEO) taken during Expedition 8

NASA Image and Video Library

2004-01-06

ISS008-E-12109 (6 January 2004) --- Five year old icebergs near South Georgia Island are featured in this image photographed by an Expedition 8 crewmember onboard the International Space Station (ISS). This oblique image shows two pieces of a massive iceberg that broke off from the Antarctica Ronne Ice Shelf in October 1998. The pieces of iceberg A-38 have floated relatively close to South Georgia Island. After five years and 3 months, they are approximately 1500 nautical miles from their origin. The cloud pattern is indicative of the impact of the mountainous islands on the local wind field. At the time this image was taken, the icebergs were sheltered in the lee side of the island.

Marine Layer Clouds off the California Coast

NASA Image and Video Library

2017-12-08

NASA image acquired September 27, 2012 On September 27, 2012, the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite captured this nighttime view of low-lying marine layer clouds along the coast of California. The image was captured by the VIIRS “day-night band,” which detects light in a range of wavelengths from green to near-infrared and uses filtering techniques to observe signals such as gas flares, auroras, wildfires, city lights, and reflected moonlight. An irregularly-shaped patch of high clouds hovers off the coast of California, and moonlight caused the high clouds to cast distinct shadows on the marine layer clouds below. VIIRS acquired the image when the Moon was in its waxing gibbous phase, meaning it was more than half-lit, but less than full. Low clouds pose serious hazards for air and ship traffic, but satellites have had difficulty detecting them in the past. To illustrate this, the second image shows the same scene in thermal infrared, the band that meteorologists generally use to monitor clouds at night. Only high clouds are visible; the low clouds do not show up at all because they are roughly the same temperature as the ground. NASA Earth Observatory image by Jesse Allen and Robert Simmon, using VIIRS Day-Night Band data from the Suomi National Polar-orbiting Partnership. Suomi NPP is the result of a partnership between NASA, the National Oceanic and Atmospheric Administration, and the Department of Defense. Caption by Adam Voiland. Instrument: Suomi NPP - VIIRS Credit: NASA Earth Observatory Click here to view all of the Earth at Night 2012 images Click here to read more about this image NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Tropical Depression 6 (Florence) in the Atlantic

NASA Technical Reports Server (NTRS)

2006-01-01

[figure removed for brevity, see original site] [figure removed for brevity, see original site] Microwave ImageVisible Light Image

These infrared, microwave, and visible images were created with data retrieved by the Atmospheric Infrared Sounder (AIRS) on NASA's Aqua satellite.

Infrared Image Because infrared radiation does not penetrate through clouds, AIRS infrared images show either the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures (in purple) are associated with high, cold cloud tops that make up the top of the storm. In cloud-free areas the AIRS instrument will receive the infrared radiation from the surface of the Earth, resulting in the warmest temperatures (orange/red).

Microwave Image AIRS data used to create the microwave images come from the microwave radiation emitted by Earth's atmosphere which is then received by the instrument. It shows where the heaviest rainfall is taking place (in blue) in the storm. Blue areas outside of the storm, where there are either some clouds or no clouds, indicate where the sea surface shines through.

Vis/NIR Image The AIRS instrument suite contains a sensor that captures light in the visible/near-infrared portion of the electromagnetic spectrum. These 'visible' images are similar to a snapshot taken with your camera.

The Atmospheric Infrared Sounder Experiment, with its visible, infrared, and microwave detectors, provides a three-dimensional look at Earth's weather. Working in tandem, the three instruments can make simultaneous observations all the way down to the Earth's surface, even in the presence of heavy clouds. With more than 2,000 channels sensing different regions of the atmosphere, the system creates a global, 3-D map of atmospheric temperature and humidity and provides information on clouds, greenhouse gases, and many other atmospheric phenomena. The AIRS Infrared Sounder Experiment flies onboard NASA's Aqua spacecraft and is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., under contract to NASA. JPL is a division of the California Institute of Technology in Pasadena.

Study on ice cloud optical thickness retrieval with MODIS IR spectral bands

NASA Astrophysics Data System (ADS)

Zhang, Hong; Li, Jun

2005-01-01

The operational Moderate-Resolution Imaging Spectroradiometer (MODIS) products for cloud properties such as cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), cloud optical thickness (COT), and cloud phase (CP) have been available for users globally. An approach to retrieve COT is investigated using MODIS infrared (IR) window spectral bands (8.5 mm, 11mm, and 12 mm). The COT retrieval from MODIS IR bands has the potential to provide microphysical properties with high spatial resolution during night. The results are compared with those from operational MODIS products derived from the visible (VIS) and near-infrared (NIR) bands during day. Sensitivity of COT to MODIS spectral brightness temperature (BT) and BT difference (BTD) values is studied. A look-up table is created from the cloudy radiative transfer model accounting for the cloud absorption and scattering for the cloud microphysical property retrieval. The potential applications and limitations are also discussed. This algorithm can be applied to the future imager systems such as Visible/Infrared Imager/Radiometer Suite (VIIRS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and Advanced Baseline Imager (ABI) on the Geostationary Operational Environmental Satellite (GOES)-R.

Geographic distribution of zonal wind and UV albedo at cloud top level from VMC camera on Venus Express: Influence of Venus topography through stationary gravity waves vertical propagation.

NASA Astrophysics Data System (ADS)

Bertaux, Jean-Loup; Khatunstsev, Igor; Hauchecorne, Alain; Markiewicz, Wojciech; Marcq, Emmanuel; Lebonnois, Sébastien; Patsaeva, Marina; Turin, Alexander

2015-04-01

UV images (at 365 nm) of Venus cloud top collected with VMC camera on board Venus Express allowed to derive a large number of wind measurements at altitude 67±2 km from tracking of cloud features in the period 2006-2012. Both manual (45,600) and digital (391,600) individual wind measurements over 127 orbits were analyzed showing various patterns with latitude and local time. A new longitude-latitude geographic map of the zonal wind shows a conspicuous region of strongly decreased zonal wind, a remarkable feature that was unknown up to now. While the average zonal wind near equator (from 5°S to 15°s) is -100.9 m/s in the longitude range 200-330°, it reaches -83.4 m/s in the range 60-100°, a difference of 17.5 m/s. When compared to the altimetry map of Venus, it is found that the zonal wind pattern is well correlated with the underlying relief in the region of Aphrodite Terra, with a downstream shift of about 30° (˜3,200 km). We interpret this pattern as the result of stationary gravity waves produced at ground level by the up lift of air when the horizontal wind encounters a mountain slope. These waves can propagate up to cloud top level, break there and transfer their momentum to the zonal flow. A similar phenomenon is known to operate on Earth with an influence on mesospheric winds. The LMD-GCM for Venus was run with or without topography, with and without a parameterization of gravity waves and does not display such an observed change of velocity near equator. The cloud albedo map at 365 nm varies also in longitude and latitude. We speculate that it might be the result of increased vertical mixing associated to wave breaking, and decreased abundance of the UV absorber which makes the contrast in images. The impact of these new findings on current super rotation theories remains to be assessed. This work was triggered by the presence of a conspicuous peak at 117 days in a time series of wind measurements. This is the length of the solar day as seen at the ground of Venus. Since VMC measurements are done preferably in a local time window centred on the sub-solar point, any parameter having a geographic longitude dependence will show a peak at 117 days.

OpenID connect as a security service in Cloud-based diagnostic imaging systems

NASA Astrophysics Data System (ADS)

Ma, Weina; Sartipi, Kamran; Sharghi, Hassan; Koff, David; Bak, Peter

2015-03-01

The evolution of cloud computing is driving the next generation of diagnostic imaging (DI) systems. Cloud-based DI systems are able to deliver better services to patients without constraining to their own physical facilities. However, privacy and security concerns have been consistently regarded as the major obstacle for adoption of cloud computing by healthcare domains. Furthermore, traditional computing models and interfaces employed by DI systems are not ready for accessing diagnostic images through mobile devices. RESTful is an ideal technology for provisioning both mobile services and cloud computing. OpenID Connect, combining OpenID and OAuth together, is an emerging REST-based federated identity solution. It is one of the most perspective open standards to potentially become the de-facto standard for securing cloud computing and mobile applications, which has ever been regarded as "Kerberos of Cloud". We introduce OpenID Connect as an identity and authentication service in cloud-based DI systems and propose enhancements that allow for incorporating this technology within distributed enterprise environment. The objective of this study is to offer solutions for secure radiology image sharing among DI-r (Diagnostic Imaging Repository) and heterogeneous PACS (Picture Archiving and Communication Systems) as well as mobile clients in the cloud ecosystem. Through using OpenID Connect as an open-source identity and authentication service, deploying DI-r and PACS to private or community clouds should obtain equivalent security level to traditional computing model.

Mean winds at the cloud top of Venus obtained from two-wavelength UV imaging by Akatsuki

NASA Astrophysics Data System (ADS)

Horinouchi, Takeshi; Kouyama, Toru; Lee, Yeon Joo; Murakami, Shin-ya; Ogohara, Kazunori; Takagi, Masahiro; Imamura, Takeshi; Nakajima, Kensuke; Peralta, Javier; Yamazaki, Atsushi; Yamada, Manabu; Watanabe, Shigeto

2018-01-01

Venus is covered with thick clouds. Ultraviolet (UV) images at 0.3-0.4 microns show detailed cloud features at the cloud-top level at about 70 km, which are created by an unknown UV-absorbing substance. Images acquired in this wavelength range have traditionally been used to measure winds at the cloud top. In this study, we report low-latitude winds obtained from the images taken by the UV imager, UVI, onboard the Akatsuki orbiter from December 2015 to March 2017. UVI provides images with two filters centered at 365 and 283 nm. While the 365-nm images enable continuation of traditional Venus observations, the 283-nm images visualize cloud features at an SO2 absorption band, which is novel. We used a sophisticated automated cloud-tracking method and thorough quality control to estimate winds with high precision. Horizontal winds obtained from the 283-nm images are generally similar to those from the 365-nm images, but in many cases, westward winds from the former are faster than the latter by a few m/s. From previous studies, one can argue that the 283-nm images likely reflect cloud features at higher altitude than the 365-nm images. If this is the case, the superrotation of the Venusian atmosphere generally increases with height at the cloud-top level, where it has been thought to roughly peak. The mean winds obtained from the 365-nm images exhibit local time dependence consistent with known tidal features. Mean zonal winds exhibit asymmetry with respect to the equator in the latter half of the analysis period, significantly at 365 nm and weakly at 283 nm. This contrast indicates that the relative altitude may vary with time and latitude, and so are the observed altitudes. In contrast, mean meridional winds do not exhibit much long-term variability. A previous study suggested that the geographic distribution of temporal mean zonal winds obtained from UV images from the Venus Express orbiter during 2006-2012 can be interpreted as forced by topographically induced stationary gravity waves. However, the geographic distribution of temporal mean zonal winds we obtained is not consistent with that distribution, which suggests that the distribution may not be persistent. [Figure not available: see fulltext.

Coupling of Clouds and Moisture Transport in Extratropical Cyclonic Systems and the Associated Atmospheric Heating (Q1) and Moisture Sink (Q2)

NASA Astrophysics Data System (ADS)

Wong, S.; Naud, C. M.; Kahn, B. H.; Wu, L.; Fetzer, E. J.

2017-12-01

Different sectors in extratropical cyclonic systems (ETCs) exhibit various patterns in atmospheric moisture transport and provide an excellent test bed for studying coupling between cloud processes and large-scale circulation. Large-scale atmospheric moisture transport diagnosed from the Modern-Era Retrospective analysis for Research and Applications Version 2 and cloud properties (cloud top pressure and optical depth, cloud effective radii and thermodynamic phase) from both the Moderate Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) will be composited around Northern Hemispheric ETCs over ocean according to their stages of development. Atmospheric diabatic heating rates (Q1) and moisture sinks (Q2) are also inferred from the reanalysis winds, temperature, and specific humidity. Across the warm fronts, elevated convection in the pre-warm front regime is associated with frequent stratiform clouds with middle-to-upper tropospheric heating and lower tropospheric cooling, while upright convection in the warm front regime has frequent deep convective clouds with free-tropospheric heating and strong boundary layer cooling. Thinner stratiform and cirrus clouds are evident in the warm sector with top-heavy profiles of rising motion and diabatic heating. Moisture advection exhibits a sharp gradient across the cold fronts, with convection in the pre-cold front regime highly dependent on the stage of the ETC development. Heating in the boundary layers of the cold sector, polar-air intrusion, and pre-warm sector regimes depends on the amount of low-level clouds, which is again modulated by the stage of the ETC development.

Retrieving the Polar Mixed-Phase Cloud Liquid Water Path by Combining CALIOP and IIR Measurements

NASA Astrophysics Data System (ADS)

Luo, Tao; Wang, Zhien; Li, Xuebin; Deng, Shumei; Huang, Yong; Wang, Yingjian

2018-02-01

Mixed-phase cloud (MC) is the dominant cloud type over the polar region, and there are challenging conditions for remote sensing and in situ measurements. In this study, a new methodology of retrieving the stratiform MC liquid water path (LWP) by combining Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and infrared imaging radiometer (IIR) measurements was developed and evaluated. This new methodology takes the advantage of reliable cloud-phase discrimination by combining lidar and radar measurements. An improved multiple-scattering effect correction method for lidar signals was implemented to provide reliable cloud extinction near cloud top. Then with the adiabatic cloud assumption, the MC LWP can be retrieved by a lookup-table-based method. Simulations with error-free inputs showed that the mean bias and the root mean squared error of the LWP derived from the new method are -0.23 ± 2.63 g/m2, with the mean absolute relative error of 4%. Simulations with erroneous inputs suggested that the new methodology could provide reliable retrieval of LWP to support the statistical or climatology analysis. Two-month A-train satellite retrievals over Arctic region showed that the new method can produce very similar cloud top temperature (CTT) dependence of LWP to the ground-based microwave radiometer measurements, with a bias of -0.78 g/m2 and a correlation coefficient of 0.95 between the two mean CTT-LWP relationships. The new approach can also produce reasonable pattern and value of LWP in spatial distribution over the Arctic region.

Validation of Cloud Properties From Multiple Satellites Using CALIOP Data

NASA Technical Reports Server (NTRS)

Yost, Christopher R.; Minnis, Patrick; Bedka, Kristopher M.; Heck, Patrick W.; Palikonda, Rabindra; Sun-Mack, Sunny; Trepte, Qing

2016-01-01

The NASA Langley Satellite ClOud and Radiative Property retrieval System (SatCORPS) is routinely applied to multispectral imagery from several geostationary and polar-orbiting imagers to retrieve cloud properties for weather and climate applications. Validation of the retrievals with independent datasets is continuously ongoing in order to understand differences caused by calibration, spatial resolution, viewing geometry, and other factors. The CALIOP instrument provides a decade of detailed cloud observations which can be used to evaluate passive imager retrievals of cloud boundaries, thermodynamic phase, cloud optical depth, and water path on a global scale. This paper focuses on comparisons of CALIOP retrievals to retrievals from MODIS, VIIRS, AVHRR, GOES, SEVIRI, and MTSAT. CALIOP is particularly skilled at detecting weakly-scattering cirrus clouds with optical depths less than approx. 0.5. These clouds are often undetected by passive imagers and the effect this has on the property retrievals is discussed.

Automated cloud classification using a ground based infra-red camera and texture analysis techniques

NASA Astrophysics Data System (ADS)

Rumi, Emal; Kerr, David; Coupland, Jeremy M.; Sandford, Andrew P.; Brettle, Mike J.

2013-10-01

Clouds play an important role in influencing the dynamics of local and global weather and climate conditions. Continuous monitoring of clouds is vital for weather forecasting and for air-traffic control. Convective clouds such as Towering Cumulus (TCU) and Cumulonimbus clouds (CB) are associated with thunderstorms, turbulence and atmospheric instability. Human observers periodically report the presence of CB and TCU clouds during operational hours at airports and observatories; however such observations are expensive and time limited. Robust, automatic classification of cloud type using infrared ground-based instrumentation offers the advantage of continuous, real-time (24/7) data capture and the representation of cloud structure in the form of a thermal map, which can greatly help to characterise certain cloud formations. The work presented here utilised a ground based infrared (8-14 μm) imaging device mounted on a pan/tilt unit for capturing high spatial resolution sky images. These images were processed to extract 45 separate textural features using statistical and spatial frequency based analytical techniques. These features were used to train a weighted k-nearest neighbour (KNN) classifier in order to determine cloud type. Ground truth data were obtained by inspection of images captured simultaneously from a visible wavelength colour camera at the same installation, with approximately the same field of view as the infrared device. These images were classified by a trained cloud observer. Results from the KNN classifier gave an encouraging success rate. A Probability of Detection (POD) of up to 90% with a Probability of False Alarm (POFA) as low as 16% was achieved.

Comparison of CERES Cloud Properties Derived from Aqua and Terra MODIS Data and TRMM VIRS Radiances

NASA Astrophysics Data System (ADS)

Minnis, P.; Young, D. F.; Sun-Mack, S.; Trepte, Q. Z.; Chen, Y.; Heck, P. W.; Wielicki, B. A.

2003-12-01

The Clouds and Earth's Radiant Energy System (CERES) Project is obtaining Earth radiation budget measurements of unprecedented accuracy as a result of improved instruments and an analysis system that combines simultaneous, high-resolution cloud property retrievals with the broadband radiance data. The cloud properties are derived from three different satellite imagers: the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) and the Moderate Resolution Imaging Spectroradiometers (MODIS) on the Aqua and Terra satellites. A single set of consistent algorithms using the 0.65, 1.6 or 2.1, 3.7, 10.8, and 12.0-æm channels are applied to all three imagers. The cloud properties include, cloud coverage, height, thickness, temperature, optical depth, phase, effective particle size, and liquid or ice water path. Because each satellite is in a different orbit, the results provide information on the diurnal cycle of cloud properties. Initial intercalibrations show excellent consistency between the three images except for some differences of ~ 1K between the 3.7-æm channel on Terra and those on VIRS and Aqua. The derived cloud properties are consistent with the known diurnal characteristics of clouds in different areas. These datasets should be valuable for exploring the role of clouds in the radiation budget and hydrological cycle.

Continental land cover classification using meteorological satellite data

NASA Technical Reports Server (NTRS)

Tucker, C. J.; Townshend, J. R. G.; Goff, T. E.

1983-01-01

The use of the National Oceanic and Atmospheric Administration's advanced very high resolution radiometer satellite data for classifying land cover and monitoring of vegetation dynamics over an extremely large area is demonstrated for the continent of Africa. Data from 17 imaging periods of 21 consecutive days each were composited by a technique sensitive to the in situ green-leaf biomass to provide cloud-free imagery for the whole continent. Virtually cloud-free images were obtainable even for equatorial areas. Seasonal variation in the density and extent of green leaf vegetation corresponded to the patterns of rainfall associated with the inter-tropical convergence zone. Regional variations, such as the 1982 drought in east Africa, were also observed. Integration of the weekly satellite data with respect to time produced a remotely sensed assessment of biological activity based upon density and duration of green-leaf biomass. Two of the 21-day composited data sets were used to produce a general land cover classification. The resultant land cover distributions correspond well to those of existing maps.

OpenID Connect as a security service in cloud-based medical imaging systems

PubMed Central

Ma, Weina; Sartipi, Kamran; Sharghigoorabi, Hassan; Koff, David; Bak, Peter

2016-01-01

Abstract. The evolution of cloud computing is driving the next generation of medical imaging systems. However, privacy and security concerns have been consistently regarded as the major obstacles for adoption of cloud computing by healthcare domains. OpenID Connect, combining OpenID and OAuth together, is an emerging representational state transfer-based federated identity solution. It is one of the most adopted open standards to potentially become the de facto standard for securing cloud computing and mobile applications, which is also regarded as “Kerberos of cloud.” We introduce OpenID Connect as an authentication and authorization service in cloud-based diagnostic imaging (DI) systems, and propose enhancements that allow for incorporating this technology within distributed enterprise environments. The objective of this study is to offer solutions for secure sharing of medical images among diagnostic imaging repository (DI-r) and heterogeneous picture archiving and communication systems (PACS) as well as Web-based and mobile clients in the cloud ecosystem. The main objective is to use OpenID Connect open-source single sign-on and authorization service and in a user-centric manner, while deploying DI-r and PACS to private or community clouds should provide equivalent security levels to traditional computing model. PMID:27340682

A Cut in the Clouds

NASA Image and Video Library

2017-12-08

Like a ship carving its way through the sea, the South Georgia and South Sandwich Islands parted the clouds. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite acquired this natural-color image on February 2, 2017. The ripples in the clouds are known as gravity waves. NASA image by Jeff Schmaltz, LANCE/EOSDIS Rapid Response #nasagoddard

Automatic registration of fused lidar/digital imagery (texel images) for three-dimensional image creation

NASA Astrophysics Data System (ADS)

Budge, Scott E.; Badamikar, Neeraj S.; Xie, Xuan

2015-03-01

Several photogrammetry-based methods have been proposed that the derive three-dimensional (3-D) information from digital images from different perspectives, and lidar-based methods have been proposed that merge lidar point clouds and texture the merged point clouds with digital imagery. Image registration alone has difficulty with smooth regions with low contrast, whereas point cloud merging alone has difficulty with outliers and a lack of proper convergence in the merging process. This paper presents a method to create 3-D images that uses the unique properties of texel images (pixel-fused lidar and digital imagery) to improve the quality and robustness of fused 3-D images. The proposed method uses both image processing and point-cloud merging to combine texel images in an iterative technique. Since the digital image pixels and the lidar 3-D points are fused at the sensor level, more accurate 3-D images are generated because registration of image data automatically improves the merging of the point clouds, and vice versa. Examples illustrate the value of this method over other methods. The proposed method also includes modifications for the situation where an estimate of position and attitude of the sensor is known, when obtained from low-cost global positioning systems and inertial measurement units sensors.

Infrared Cloud Imager Development for Atmospheric Optical Communication Characterization, and Measurements at the JPL Table Mountain Facility

NASA Astrophysics Data System (ADS)

Nugent, P. W.; Shaw, J. A.; Piazzolla, S.

2013-02-01

The continuous demand for high data return in deep space and near-Earth satellite missions has led NASA and international institutions to consider alternative technologies for high-data-rate communications. One solution is the establishment of wide-bandwidth Earth-space optical communication links, which require (among other things) a nearly obstruction-free atmospheric path. Considering the atmospheric channel, the most common and most apparent impairments on Earth-space optical communication paths arise from clouds. Therefore, the characterization of the statistical behavior of cloud coverage for optical communication ground station candidate sites is of vital importance. In this article, we describe the development and deployment of a ground-based, long-wavelength infrared cloud imaging system able to monitor and characterize the cloud coverage. This system is based on a commercially available camera with a 62-deg diagonal field of view. A novel internal-shutter-based calibration technique allows radiometric calibration of the camera, which operates without a thermoelectric cooler. This cloud imaging system provides continuous day-night cloud detection with constant sensitivity. The cloud imaging system also includes data-processing algorithms that calculate and remove atmospheric emission to isolate cloud signatures, and enable classification of clouds according to their optical attenuation. Measurements of long-wavelength infrared cloud radiance are used to retrieve the optical attenuation (cloud optical depth due to absorption and scattering) in the wavelength range of interest from visible to near-infrared, where the cloud attenuation is quite constant. This article addresses the specifics of the operation, calibration, and data processing of the imaging system that was deployed at the NASA/JPL Table Mountain Facility (TMF) in California. Data are reported from July 2008 to July 2010. These data describe seasonal variability in cloud cover at the TMF site, with cloud amount (percentage of cloudy pixels) peaking at just over 51 percent during February, of which more than 60 percent had optical attenuation exceeding 12 dB at wavelengths in the range from the visible to the near-infrared. The lowest cloud amount was found during August, averaging 19.6 percent, and these clouds were mostly optically thin, with low attenuation.

Bands of Clouds and Lace

NASA Image and Video Library

2004-05-13

As Cassini nears its rendezvous with Saturn, new detail in the banded clouds of the planet's atmosphere are becoming visible. Cassini began the journey to the ringed world of Saturn nearly seven years ago and is now less than two months away from orbit insertion on June 30. Cassini’s narrow-angle camera took this image on April 16, 2004, when the spacecraft was 38.5 million kilometers (23.9 million miles) from Saturn. Dark regions are generally areas free of high clouds, and bright areas are places with high, thick clouds which shield the view of the darker areas below. A dark spot is visible at the south pole, which is remarkable to scientists because it is so small and centered. The spot could be affected by Saturn's magnetic field, which is nearly aligned with the planet's rotation axis, unlike the magnetic fields of Jupiter and Earth. From south to north, other notable features are the two white spots just above the dark spot toward the right, and the large dark oblong-shaped feature that extends across the middle. The darker band beneath the oblong-shaped feature has begun to show a lacy pattern of lighter-colored, high altitude clouds, indicative of turbulent atmospheric conditions. The cloud bands move at different speeds, and their irregularities may be due to either the different motions between them or to disturbances below the visible cloud layer. Such disturbances might be powered by the planet's internal heat; Saturn radiates more energy than it receives from the Sun. The moon Mimas (396 kilometers, 245 miles across) is visible to the left of the south pole. Saturn currently has 31 known moons. Since launch, 13 new moons have been discovered by ground-based telescopes. Cassini will get a closer look and may discover new moons, perhaps embedded within the planet’s magnificent rings. This image was taken using a filter sensitive to light near 727 nanometers, one of the near-infrared absorption bands of methane gas, which is one of the ingredients in Saturn's atmosphere. The image scale is approximately 231 kilometers (144 miles) per pixel. Contrast has been enhanced to aid visibility of features in the atmosphere. http://photojournal.jpl.nasa.gov/catalog/PIA05391

Observed correlation of Venus topography with the zonal wind and albedo at cloud top level: the role of stationary gravity waves.

NASA Astrophysics Data System (ADS)

Bertaux, Jean-Loup; Khatunstsev, Igor; Hauchecorne, Alain; Markiewicz, Wojtek; Emmanuel, Marcq; Sébastien, Lebonnois; Marina, Patsaeva; Alex, Turin; Anna, Fedorova

2016-04-01

Based on the analysis of UV images (at 365 nm) of Venus cloud top (altitude 67±2 km) collected with VMC (Venus Monitoring Camera) on board Venus Express (VEX), it is found that the zonal wind speed south of the equator (from 5°S to 15°s) shows a conspicuous variation (from -101 to -83 m/s) with geographic longitude of Venus, correlated with the underlying relief of Aphrodite Terra. We interpret this pattern as the result of stationary gravity waves produced at ground level by the up lift of air when the horizontal wind encounters a mountain slope. These waves can propagate up to cloud top level, break there and transfer their momentum to the zonal flow. Such upward propagation of gravity waves and influence on the wind speed vertical profile was shown to play an important role in the middle atmosphere of the Earth by Lindzen [1981], but is not reproduced in a current GCM of Venus atmosphere. Consistent with present findings, the two VEGA mission balloons experienced a small, but significant, difference of westward velocity, at their 53 km floating altitude. The albedo at 365 nm varies also with longitude and latitude in a pattern strikingly similar in the low latitude regions to a recent map of cloud top H2O [Fedorova et al., 2015], in which a lower UV albedo is correlated with increased H2O. We argue that H2O enhancement is the sign of upwelling, suggesting that the UV absorber is also brought to cloud top by upwelling.

Understanding the Spatiotemporal Structures in Atmosphere-Land Surface Exchange at the Jülich Observatory for Cloud Evolution

NASA Astrophysics Data System (ADS)

Marke, T.; Crewell, S.; Loehnert, U.; Rascher, U.; Schween, J. H.

2015-12-01

This study aims at identifying spatial and temporal patterns of surface-atmosphere exchange parameters from highly-resolved and long-term observations. For this purpose, a combination of continuous ground-based measurements and dedicated aircraft campaigns using state-of-the-art remote sensing instrumentation at the Jülich Observatory for Cloud Evolution (JOYCE) is available. JOYCE provides a constantly growing multi-year data set for detailed insight into boundary layer processes and patterns related to surface conditions since 2011. The JOYCE site is embedded in a rural environment with different crop types. The availability of a scanning microwave radiometer and cloud radar is a unique component of JOYCE. The hemispheric scans of the ground-based radiometer allow the identification and quantification of horizontal gradients in water vapor and liquid water path measurements. How these gradients are connected to near-surface fluxes and the topography depending on the mean wind flow and surface fluxes is investigated by exploring the long-term data set. Additionally, situations with strong coupling to the surface can be identified by observing the atmospheric turbulence and stability within the boundary layer, using different lidar systems. Furthermore, the influence of thin liquid water clouds, which are typical for the boundary layer development, on the radiation field and the interaction with the vegetation is examined. Applying a synergistic statistical retrieval approach, using passive microwave and infrared observations, shows an improvement in retrieving thin liquid cloud microphysical properties. The role of vegetation is assessed by exploiting the time series of the sun-induced chlorophyll fluorescence (SIF) signal measured at the ground level using automated measurements. For selected case studies, a comparison to maps of hyperspectral reflectance and SIF obtained from an airborne high-resolution imaging spectrometer is realized.

IRAS images of nearby dark clouds

NASA Technical Reports Server (NTRS)

Wood, Douglas O. S.; Myers, Philip C.; Daugherty, Debra A.

1994-01-01

We have investigated approximately 100 nearby molecular clouds using the extensive, all-sky database of IRAS. The clouds in this study cover a wide range of physical properties including visual extinction, size, mass, degree of isolation, homogeneity and morphology. IRAS 100 and 60 micron co-added images were used to calculate the 100 micron optical depth of dust in the clouds. These images of dust optical depth compare very well with (12)CO and (13)CO observations, and can be related to H2 column density. From the optical depth images we locate the edges of dark clouds and the dense cores inside them. We have identified a total of 43 `IRAS clouds' (regions with A(sub v) greater than 2) which contain a total of 255 `IRAS cores' (regions with A(sub v) greater than 4) and we catalog their physical properties. We find that the clouds are remarkably filamentary, and that the cores within the clouds are often distributed along the filaments. The largest cores are usually connected to other large cores by filaments. We have developed selection criteria to search the IRAS Point Source Catalog for stars that are likely to be associated with the clouds and we catalog the IRAS sources in each cloud or core. Optically visible stars associated with the clouds have been identified from the Herbig and Bell catalog. From these data we characterize the physical properties of the clouds including their star-formation efficiency.

Venus winds from ultraviolet, visible and near infrared images from the VIRTIS instrument on Venus Express

NASA Astrophysics Data System (ADS)

Hueso, Ricardo; Garate-Lopez, I.; Peralta, J.; Bandos, T.; Sánchez-Lavega, A.

2013-10-01

After more than 6 years orbiting Venus the Venus Express mission has provided the largest database of observations of Venus atmosphere at different cloud layers with the combination of VMC and VIRTIS instruments. We present measurements of cloud motions in the South hemisphere of Venus analyzing images from the VIRTIS-M visible channel at different wavelengths sensitive to the upper cloud haze at 65-70 km height (dayside ultraviolet images) and the middle cloud deck (dayside visible and near infrared images around 1 μm) about 5-8 km deeper in the atmosphere. We combine VIRTIS images in nearby wavelengths to increase the contrast of atmospheric details and measurements were obtained with a semi-automatic cloud correlation algorithm. Both cloud layers are studied simultaneously to infer similarities and differences in these vertical levels in terms of cloud morphologies and winds. For both levels we present global mean zonal and meridional winds, latitudinal distribution of winds with local time and the wind shear between both altitudes. The upper branch of the Hadley cell circulation is well resolved in UV images with an acceleration of the meridional circulation at mid-latitudes with increasing local time peaking at 14-16h. This organized meridional circulation is almost absent in NIR images. Long-term variability of zonal winds is also found in UV images with increasing winds over time during the VEX mission. This is in agreement with current analysis of VMC images (Kathuntsev et al. 2013). The possible long-term acceleration of zonal winds is also examined for NIR images. References Khatuntsev et al. Icarus 226, 140-158 (2013)

A hybrid approach to estimate the complex motions of clouds in sky images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peng, Zhenzhou; Yu, Dantong; Huang, Dong

Tracking the motion of clouds is essential to forecasting the weather and to predicting the short-term solar energy generation. Existing techniques mainly fall into two categories: variational optical flow, and block matching. In this article, we summarize recent advances in estimating cloud motion using ground-based sky imagers and quantitatively evaluate state-of-the-art approaches. Then we propose a hybrid tracking framework to incorporate the strength of both block matching and optical flow models. To validate the accuracy of the proposed approach, we introduce a series of synthetic images to simulate the cloud movement and deformation, and thereafter comprehensively compare our hybrid approachmore » with several representative tracking algorithms over both simulated and real images collected from various sites/imagers. The results show that our hybrid approach outperforms state-of-the-art models by reducing at least 30% motion estimation errors compared with the ground-truth motions in most of simulated image sequences. Furthermore, our hybrid model demonstrates its superior efficiency in several real cloud image datasets by lowering at least 15% Mean Absolute Error (MAE) between predicted images and ground-truth images.« less

A hybrid approach to estimate the complex motions of clouds in sky images

DOE PAGES

Peng, Zhenzhou; Yu, Dantong; Huang, Dong; ...

2016-09-14

Tracking the motion of clouds is essential to forecasting the weather and to predicting the short-term solar energy generation. Existing techniques mainly fall into two categories: variational optical flow, and block matching. In this article, we summarize recent advances in estimating cloud motion using ground-based sky imagers and quantitatively evaluate state-of-the-art approaches. Then we propose a hybrid tracking framework to incorporate the strength of both block matching and optical flow models. To validate the accuracy of the proposed approach, we introduce a series of synthetic images to simulate the cloud movement and deformation, and thereafter comprehensively compare our hybrid approachmore » with several representative tracking algorithms over both simulated and real images collected from various sites/imagers. The results show that our hybrid approach outperforms state-of-the-art models by reducing at least 30% motion estimation errors compared with the ground-truth motions in most of simulated image sequences. Furthermore, our hybrid model demonstrates its superior efficiency in several real cloud image datasets by lowering at least 15% Mean Absolute Error (MAE) between predicted images and ground-truth images.« less

CloudSat Profiles Tropical Storm Andrea

NASA Image and Video Library

2007-05-10

CloudSat's Cloud Profiling Radar captured a profile across Tropical Storm Andrea on Wednesday, May 9, 2007, near the South Carolina/Georgia/Florida Atlantic coast. The upper image shows an infrared view of Tropical Storm Andrea from the Moderate Resolution Imaging Spectroradiometer instrument on NASA's Aqua satellite, with CloudSat's ground track shown as a red line. The lower image is the vertical cross section of radar reflectivity along this path, where the colors indicate the intensity of the reflected radar energy. CloudSat orbits approximately one minute behind Aqua in a satellite formation known as the A-Train. http://photojournal.jpl.nasa.gov/catalog/PIA09379

Tropical Depression Debbie in the Atlantic

NASA Technical Reports Server (NTRS)

2006-01-01

[figure removed for brevity, see original site] [figure removed for brevity, see original site] Microwave ImageVisible Light Image

Infrared Image These images show Tropical Depression Debbie in the Atlantic, from the Atmospheric Infrared Sounder (AIRS) on NASA's Aqua satellite on August 22, 2006. This AIRS image shows the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures (in purple) are associated with high, cold cloud tops that make up the top of the storm. The infrared signal does not penetrate through clouds. Where there are no clouds the AIRS instrument reads the infrared signal from the surface of the Earth, revealing warmer temperatures (red). At the time the data were taken from which these images were made the eye had not yet opened but the storm is now well organized. The location of the future eye appears as a circle at 275 K brightness temperature in the microwave image just to the SE of the Azores.

Microwave Image The microwave image is created from microwave radiation emitted by Earth's atmosphere and received by the instrument. It shows where the heaviest rainfall is taking place (in blue) in the storm. Blue areas outside of the storm where there are either some clouds or no clouds, indicate where the sea surface shines through.

Vis/NIR Image Tropical Depression Debbie captured by the visible light/near-infrared sensor on the AIRS instrument.

The Atmospheric Infrared Sounder Experiment, with its visible, infrared, and microwave detectors, provides a three-dimensional look at Earth's weather. Working in tandem, the three instruments can make simultaneous observations all the way down to the Earth's surface, even in the presence of heavy clouds. With more than 2,000 channels sensing different regions of the atmosphere, the system creates a global, 3-D map of atmospheric temperature and humidity and provides information on clouds, greenhouse gases, and many other atmospheric phenomena. The AIRS Infrared Sounder Experiment flies onboard NASA's Aqua spacecraft and is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., under contract to NASA. JPL is a division of the California Institute of Technology in Pasadena.

NOAA-L satellite arrives at Vandenberg AFB

NASA Technical Reports Server (NTRS)

2000-01-01

A crated National Oceanic and Atmospheric Administration (NOAA-L) satellite arrives at Vandenberg Air Force Base, Calif. It is part of the Polar-Orbiting Operational Environmental Satellite (POES) program that provides atmospheric measurements of temperature, humidity, ozone and cloud images, tracking weather patterns that affect the global weather and climate. The launch of the NOAA-L satellite is scheduled no earlier than Sept. 12 aboard a Lockheed Martin Titan II rocket. KSC00vafbdig007

NASA Image and Video Library

2000-06-30

At the launch tower, Vandenberg Air Force Base, Calif., the second stage of a Titan II rocket is lifted to vertical. The Titan will power the launch of a National Oceanic and Atmospheric Administration (NOAA-L) satellite scheduled no earlier than Sept. 12. NOAA-L is part of the Polar-Orbiting Operational Environmental Satellite (POES) program that provides atmospheric measurements of temperature, humidity, ozone and cloud images, tracking weather patterns that affect the global weather and climate

Influence of Ice Cloud Microphysics on Imager-Based Estimates of Earth's Radiation Budget

NASA Astrophysics Data System (ADS)

Loeb, N. G.; Kato, S.; Minnis, P.; Yang, P.; Sun-Mack, S.; Rose, F. G.; Hong, G.; Ham, S. H.

2016-12-01

A central objective of the Clouds and the Earth's Radiant Energy System (CERES) is to produce a long-term global climate data record of Earth's radiation budget from the TOA down to the surface along with the associated atmospheric and surface properties that influence it. CERES relies on a number of data sources, including broadband radiometers measuring incoming and reflected solar radiation and OLR, high-resolution spectral imagers, meteorological, aerosol and ozone assimilation data, and snow/sea-ice maps based on microwave radiometer data. While the TOA radiation budget is largely determined directly from accurate broadband radiometer measurements, the surface radiation budget is derived indirectly through radiative transfer model calculations initialized using imager-based cloud and aerosol retrievals and meteorological assimilation data. Because ice cloud particles exhibit a wide range of shapes, sizes and habits that cannot be independently retrieved a priori from passive visible/infrared imager measurements, assumptions about the scattering properties of ice clouds are necessary in order to retrieve ice cloud optical properties (e.g., optical depth) from imager radiances and to compute broadband radiative fluxes. This presentation will examine how the choice of an ice cloud particle model impacts computed shortwave (SW) radiative fluxes at the top-of-atmosphere (TOA) and surface. The ice cloud particle models considered correspond to those from prior, current and future CERES data product versions. During the CERES Edition2 (and Edition3) processing, ice cloud particles were assumed to be smooth hexagonal columns. In the Edition4, roughened hexagonal columns are assumed. The CERES team is now working on implementing in a future version an ice cloud particle model comprised of a two-habit ice cloud model consisting of roughened hexagonal columns and aggregates of roughened columnar elements. In each case, we use the same ice particle model in both the imager-based cloud retrievals (inverse problem) and the computed radiative fluxes (forward calculation). In addition to comparing radiative fluxes using the different ice cloud particle models, we also compare instantaneous TOA flux calculations with those observed by the CERES instrument.

Classification by Using Multispectral Point Cloud Data

NASA Astrophysics Data System (ADS)

Liao, C. T.; Huang, H. H.

2012-07-01

Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

False Color Mosaic Great Red Spot

NASA Technical Reports Server (NTRS)

1996-01-01

False color representation of Jupiter's Great Red Spot (GRS) taken through three different near-infrared filters of the Galileo imaging system and processed to reveal cloud top height. Images taken through Galileo's near-infrared filters record sunlight beyond the visible range that penetrates to different depths in Jupiter's atmosphere before being reflected by clouds. The Great Red Spot appears pink and the surrounding region blue because of the particular color coding used in this representation. Light reflected by Jupiter at a wavelength (886 nm) where methane strongly absorbs is shown in red. Due to this absorption, only high clouds can reflect sunlight in this wavelength. Reflected light at a wavelength (732 nm) where methane absorbs less strongly is shown in green. Lower clouds can reflect sunlight in this wavelength. Reflected light at a wavelength (757 nm) where there are essentially no absorbers in the Jovian atmosphere is shown in blue: This light is reflected from the deepest clouds. Thus, the color of a cloud in this image indicates its height. Blue or black areas are deep clouds; pink areas are high, thin hazes; white areas are high, thick clouds. This image shows the Great Red Spot to be relatively high, as are some smaller clouds to the northeast and northwest that are surprisingly like towering thunderstorms found on Earth. The deepest clouds are in the collar surrounding the Great Red Spot, and also just to the northwest of the high (bright) cloud in the northwest corner of the image. Preliminary modeling shows these cloud heights vary over 30 km in altitude. This mosaic, of eighteen images (6 in each filter) taken over a 6 minute interval during the second GRS observing sequence on June 26, 1996, has been map-projected to a uniform grid of latitude and longitude. North is at the top.

Launched in October 1989, Galileo entered orbit around Jupiter on December 7, 1995. The spacecraft's mission is to conduct detailed studies of the giant planet, its largest moons and the Jovian magnetic environment. The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

A Multi-Year Data Set of Cloud Properties Derived for CERES from Aqua, Terra, and TRMM

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Sunny Sun-Mack; Trepte, Quinz Z.; Yan Chen; Brown, Richard R.; Gibson, Sharon C.; Heck, Michael L.; Dong, Xiquan; Xi, Baike

2007-01-01

The Clouds and Earth's Radiant Energy System (CERES) Project is producing a suite of cloud properties from high-resolution imagers on several satellites and matching them precisely with broadband radiance data to study the influence of clouds and radiation on climate. The cloud properties generally compare well with independent validation sources. Distinct differences are found between the CERES cloud properties and those derived with other algorithms from the same imager data. CERES products will be updated beginning in late 2006.

Cloud conditions for low atmospheric electricity during disturbed period after the Fukushima nuclear accident

NASA Astrophysics Data System (ADS)

Yatagai, Akiyo; Yamauchi, Masatoshi; Ishihara, Masahito; Watanabe, Akira; Murata, Ken T.

2016-04-01

The vertical (downward) component of the atmospheric electric field, or potential gradient (PG) under cloud generally reflects the electric charge distribution in the cloud. The PG data at Kakioka, 150 km southwest of the Fukushima Dai-ichi Nuclear Power Plant (FNPP1) suggested that this relation can be modified when the radioactive dust was floating in the air, and the exact relation between the weather and this modification could lead to new insight in plasma physics in the wet atmosphere. Unfortunately the detailed weather data was not available above Kakioka (only the precipitation data was available). Therefore, estimation of the cloud condition during March 2011 was strongly needed. We have developed various meteorological information links (http://www.chikyu.ac.jp/akiyo/firis/) and original radar and precipitation data will be released from the page. Here we present various radar images that we have prepared for March 2011. We prepared three-dimensional radar reflectivity of the C-band radar of JMA in every 10 minutes over all Kanto Plain centered at Tokyo and Fukushima prefecture centered at Sendai. We have released images of each altitude (1km interval) for 15th - 16thand 21th March (http://sc-web.nict.go.jp/fukushima/). The vertical structure of the rainfall is almost the same at 4km with the surface and sporadic high precipitation is observed at 6 km height for 15-16th. While, generally precipitation pattern that is similar to the surface is observed at 5km height on 21th. On the other hand, an X-band radar centered at Fukushima university is also used to know more localized raindrop patterns at zenith angle of 4 degree. We prepared 10-minutes/120m mesh precipitation patterns for March 15th, 16th, 17th, 18th, 20th, 21th, 22th and 23th. Quantitative estimate is difficult from this X-band radar, but localized structure, especially for the rain-band along Nakadori (middle valley in Fukushima prefecture), that is considered to determine the highly contaminated zone, is observed with only this X-band radar in the mid-night (JST) of 15th. We will show the movie of how precipitation systems were moved at the meeting.

Best Color Image of Jupiter's Little Red Spot

NASA Technical Reports Server (NTRS)

2007-01-01

This amazing color portrait of Jupiter's 'Little Red Spot' (LRS) combines high-resolution images from the New Horizons Long Range Reconnaissance Imager (LORRI), taken at 03:12 UT on February 27, 2007, with color images taken nearly simultaneously by the Wide Field Planetary Camera 2 (WFPC2) on the Hubble Space Telescope. The LORRI images provide details as fine as 9 miles across (15 kilometers), which is approximately 10 times better than Hubble can provide on its own. The improved resolution is possible because New Horizons was only 1.9 million miles (3 million kilometers) away from Jupiter when LORRI snapped its pictures, while Hubble was more than 500 million miles (800 million kilometers) away from the Gas Giant planet.

The Little Red Spot is the second largest storm on Jupiter, roughly 70% the size of the Earth, and it started turning red in late-2005. The clouds in the Little Red Spot rotate counterclockwise, or in the anticyclonic direction, because it is a high-pressure region. In that sense, the Little Red Spot is the opposite of a hurricane on Earth, which is a low-pressure region - and, of course, the Little Red Spot is far larger than any hurricane on Earth.

Scientists don't know exactly how or why the Little Red Spot turned red, though they speculate that the change could stem from a surge of exotic compounds from deep within Jupiter, caused by an intensification of the storm system. In particular, sulfur-bearing cloud droplets might have been propelled about 50 kilometers into the upper level of ammonia clouds, where brighter sunlight bathing the cloud tops released the red-hued sulfur embedded in the droplets, causing the storm to turn red. A similar mechanism has been proposed for the Little Red Spot's 'older brother,' the Great Red Spot, a massive energetic storm system that has persisted for over a century.

New Horizons is providing an opportunity to examine an 'infant' red storm system in detail, which may help scientists understand better how these giant weather patterns form and evolve.

Comparative Phylogeographic Analyses Illustrate the Complex Evolutionary History of Threatened Cloud Forests of Northern Mesoamerica

PubMed Central

Ornelas, Juan Francisco; Sosa, Victoria; Soltis, Douglas E.; Daza, Juan M.; González, Clementina; Soltis, Pamela S.; Gutiérrez-Rodríguez, Carla; de los Monteros, Alejandro Espinosa; Castoe, Todd A.; Bell, Charles; Ruiz-Sanchez, Eduardo

2013-01-01

Comparative phylogeography can elucidate the influence of historical events on current patterns of biodiversity and can identify patterns of co-vicariance among unrelated taxa that span the same geographic areas. Here we analyze temporal and spatial divergence patterns of cloud forest plant and animal species and relate them to the evolutionary history of naturally fragmented cloud forests–among the most threatened vegetation types in northern Mesoamerica. We used comparative phylogeographic analyses to identify patterns of co-vicariance in taxa that share geographic ranges across cloud forest habitats and to elucidate the influence of historical events on current patterns of biodiversity. We document temporal and spatial genetic divergence of 15 species (including seed plants, birds and rodents), and relate them to the evolutionary history of the naturally fragmented cloud forests. We used fossil-calibrated genealogies, coalescent-based divergence time inference, and estimates of gene flow to assess the permeability of putative barriers to gene flow. We also used the hierarchical Approximate Bayesian Computation (HABC) method implemented in the program msBayes to test simultaneous versus non-simultaneous divergence of the cloud forest lineages. Our results show shared phylogeographic breaks that correspond to the Isthmus of Tehuantepec, Los Tuxtlas, and the Chiapas Central Depression, with the Isthmus representing the most frequently shared break among taxa. However, dating analyses suggest that the phylogeographic breaks corresponding to the Isthmus occurred at different times in different taxa. Current divergence patterns are therefore consistent with the hypothesis of broad vicariance across the Isthmus of Tehuantepec derived from different mechanisms operating at different times. This study, coupled with existing data on divergence cloud forest species, indicates that the evolutionary history of contemporary cloud forest lineages is complex and often lineage-specific, and thus difficult to capture in a simple conservation strategy. PMID:23409165

A holistic image segmentation framework for cloud detection and extraction

NASA Astrophysics Data System (ADS)

Shen, Dan; Xu, Haotian; Blasch, Erik; Horvath, Gregory; Pham, Khanh; Zheng, Yufeng; Ling, Haibin; Chen, Genshe

2013-05-01

Atmospheric clouds are commonly encountered phenomena affecting visual tracking from air-borne or space-borne sensors. Generally clouds are difficult to detect and extract because they are complex in shape and interact with sunlight in a complex fashion. In this paper, we propose a clustering game theoretic image segmentation based approach to identify, extract, and patch clouds. In our framework, the first step is to decompose a given image containing clouds. The problem of image segmentation is considered as a "clustering game". Within this context, the notion of a cluster is equivalent to a classical equilibrium concept from game theory, as the game equilibrium reflects both the internal and external (e.g., two-player) cluster conditions. To obtain the evolutionary stable strategies, we explore three evolutionary dynamics: fictitious play, replicator dynamics, and infection and immunization dynamics (InImDyn). Secondly, we use the boundary and shape features to refine the cloud segments. This step can lower the false alarm rate. In the third step, we remove the detected clouds and patch the empty spots by performing background recovery. We demonstrate our cloud detection framework on a video clip provides supportive results.

Investigating the Use of Cloudbursts for High-Throughput Medical Image Registration

PubMed Central

Kim, Hyunjoo; Parashar, Manish; Foran, David J.; Yang, Lin

2010-01-01

This paper investigates the use of clouds and autonomic cloudbursting to support a medical image registration. The goal is to enable a virtual computational cloud that integrates local computational environments and public cloud services on-the-fly, and support image registration requests from different distributed researcher groups with varied computational requirements and QoS constraints. The virtual cloud essentially implements shared and coordinated task-spaces, which coordinates the scheduling of jobs submitted by a dynamic set of research groups to their local job queues. A policy-driven scheduling agent uses the QoS constraints along with performance history and the state of the resources to determine the appropriate size and mix of the public and private cloud resource that should be allocated to a specific request. The virtual computational cloud and the medical image registration service have been developed using the CometCloud engine and have been deployed on a combination of private clouds at Rutgers University and the Cancer Institute of New Jersey and Amazon EC2. An experimental evaluation is presented and demonstrates the effectiveness of autonomic cloudbursts and policy-based autonomic scheduling for this application. PMID:20640235

Unveiling aerosol-cloud interactions - Part 1: Cloud contamination in satellite products enhances the aerosol indirect forcing estimate

NASA Astrophysics Data System (ADS)

Christensen, Matthew W.; Neubauer, David; Poulsen, Caroline A.; Thomas, Gareth E.; McGarragh, Gregory R.; Povey, Adam C.; Proud, Simon R.; Grainger, Roy G.

2017-11-01

Increased concentrations of aerosol can enhance the albedo of warm low-level cloud. Accurately quantifying this relationship from space is challenging due in part to contamination of aerosol statistics near clouds. Aerosol retrievals near clouds can be influenced by stray cloud particles in areas assumed to be cloud-free, particle swelling by humidification, shadows and enhanced scattering into the aerosol field from (3-D radiative transfer) clouds. To screen for this contamination we have developed a new cloud-aerosol pairing algorithm (CAPA) to link cloud observations to the nearest aerosol retrieval within the satellite image. The distance between each aerosol retrieval and nearest cloud is also computed in CAPA. Results from two independent satellite imagers, the Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS), show a marked reduction in the strength of the intrinsic aerosol indirect radiative forcing when selecting aerosol pairs that are located farther away from the clouds (-0.28±0.26 W m-2) compared to those including pairs that are within 15 km of the nearest cloud (-0.49±0.18 W m-2). The larger aerosol optical depths in closer proximity to cloud artificially enhance the relationship between aerosol-loading, cloud albedo, and cloud fraction. These results suggest that previous satellite-based radiative forcing estimates represented in key climate reports may be exaggerated due to the inclusion of retrieval artefacts in the aerosol located near clouds.

Space Radar Image of North Atlantic Ocean

NASA Image and Video Library

1999-04-15

This is a radar image showing surface features on the open ocean in the northeast Atlantic Ocean. There is no land mass in this image. The purple line in the lower left of the image is the stern wake of a ship. The ship creating the wake is the bright white spot on the middle, left side of the image. The ship's wake is about 28 kilometers (17 miles) long in this image and investigators believe that is because the ship may be discharging oil. The oil makes the wake last longer and causes it to stand out in this radar image. A fairly sharp boundary or front extends from the lower left to the upper right corner of the image and separates two distinct water masses that have different temperatures. The different water temperature affects the wind patterns on the ocean. In this image, the light green area depicts rougher water with more wind, while the purple area is calmer water with less wind. The dark patches are smooth areas of low wind, probably related to clouds along the front, and the bright green patches are likely due to ice crystals in the clouds that scatter the radar waves. The overall "fuzzy" look of this image is caused by long ocean waves, also called swells. Ocean radar imagery allows the fine detail of ocean features and interactions to be seen, such as the wake, swell, ocean front and cloud effects, which can then be used to enhance the understanding of ocean dynamics on smaller and smaller scales. The image is centered at 42.8 degrees north latitude, 26.2 degrees west longitude and shows an area approximately 35 kilometers by 65 kilometers (22 by 40 miles). The colors in the image are assigned to different frequencies and polarizations of the radar as follows: red is L-band horizontally transmitted, horizontally received; green is C-band horizontally transmitted, horizontally received; blue is L-band vertically transmitted, vertically received. This image was acquired by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) imaging radar when it flew aboard the space shuttle Endeavour on April 11, 1994. SIR-C/X-SAR, a joint mission of the German, Italian and United States space agencies, is part of NASA's Mission to Planet Earth. http://photojournal.jpl.nasa.gov/catalog/PIA01799

Automated Visibility & Cloud Cover Measurements with a Solid State Imaging System

DTIC Science & Technology

1989-03-01

GL-TR-89-0061 SIO Ref. 89-7 MPL-U-26/89 AUTOMATED VISIBILITY & CLOUD COVER MEASUREMENTS WITH A SOLID-STATE IMAGING SYSTEM C) to N4 R. W. Johnson W. S...include Security Classification) Automated Visibility & Cloud Measurements With A Solid State Imaging System 12. PERSONAL AUTHOR(S) Richard W. Johnson...based imaging systems , their ics and control algorithms, thus they ar.L discussed sepa- initial deployment and the preliminary application of rately

3D Cloud Radiative Effects on Aerosol Optical Thickness Retrievals in Cumulus Cloud Fields in the Biomass Burning Region in Brazil

NASA Technical Reports Server (NTRS)

Wen, Guo-Yong; Marshak, Alexander; Cahalan, Robert F.

2004-01-01

Aerosol amount in clear regions of a cloudy atmosphere is a critical parameter in studying the interaction between aerosols and clouds. Since the global cloud cover is about 50%, cloudy scenes are often encountered in any satellite images. Aerosols are more or less transparent, while clouds are extremely reflective in the visible spectrum of solar radiation. The radiative transfer in clear-cloudy condition is highly three- dimensional (3D). This paper focuses on estimating the 3D effects on aerosol optical thickness retrievals using Monte Carlo simulations. An ASTER image of cumulus cloud fields in the biomass burning region in Brazil is simulated in this study. The MODIS products (i-e., cloud optical thickness, particle effective radius, cloud top pressure, surface reflectance, etc.) are used to construct the cloud property and surface reflectance fields. To estimate the cloud 3-D effects, we assume a plane-parallel stratification of aerosol properties in the 60 km x 60 km ASTER image. The simulated solar radiation at the top of the atmosphere is compared with plane-parallel calculations. Furthermore, the 3D cloud radiative effects on aerosol optical thickness retrieval are estimated.

Detection and Retrieval of Multi-Layered Cloud Properties Using Satellite Data

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Sun-Mack, Sunny; Chen, Yan; Yi, Helen; Huang, Jian-Ping; Nguyen, Louis; Khaiyer, Mandana M.

2005-01-01

Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.

Detection and retrieval of multi-layered cloud properties using satellite data

NASA Astrophysics Data System (ADS)

Minnis, Patrick; Sun-Mack, Sunny; Chen, Yan; Yi, Helen; Huang, Jianping; Nguyen, Louis; Khaiyer, Mandana M.

2005-10-01

Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.

Measurement of the azimuthal dependence of cross-polarized lidar returns and its relation to optical depth.

PubMed

Roy, Nathalie; Roy, Gilles; Bissonnette, Luc R; Simard, Jean-Robert

2004-05-01

We measure with a gated intensified CCD camera the cross-polarized backscattered light from a linearly polarized laser beam penetrating a cloud made of spherical particles. In accordance with previously published results we observe a clear azimuthal pattern in the recorded images. We show that the pattern is symmetrical, that it originates from second-order scattering, and that higher-order scattering causes blurring that increases with optical depth. We also find that the contrast in the symmetrical features can be related to measurement of the optical depth. Moreover, when the blurring contributions are identified and subtracted, the resulting pattern provides a pure second-order scattering measurement that can be used for retrieval of droplet size.

Enhancement of the MODIS Snow and Ice Product Suite Utilizing Image Segmentation

NASA Technical Reports Server (NTRS)

Tilton, James C.; Hall, Dorothy K.; Riggs, George A.

2006-01-01

A problem has been noticed with the current NODIS Snow and Ice Product in that fringes of certain snow fields are labeled as "cloud" whereas close inspection of the data indicates that the correct labeling is a non-cloud category such as snow or land. This occurs because the current MODIS Snow and Ice Product generation algorithm relies solely on the MODIS Cloud Mask Product for the labeling of image pixels as cloud. It is proposed here that information obtained from image segmentation can be used to determine when it is appropriate to override the cloud indication from the cloud mask product. Initial tests show that this approach can significantly reduce the cloud "fringing" in modified snow cover labeling. More comprehensive testing is required to determine whether or not this approach consistently improves the accuracy of the snow and ice product.

Automatic cloud coverage assessment of Formosat-2 image

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2011-11-01

Formosat-2 satellite equips with the high-spatial-resolution (2m ground sampling distance) remote sensing instrument. It has been being operated on the daily-revisiting mission orbit by National Space organization (NSPO) of Taiwan since May 21 2004. NSPO has also serving as one of the ground receiving stations for daily processing the received Formosat- 2 images. The current cloud coverage assessment of Formosat-2 image for NSPO Image Processing System generally consists of two major steps. Firstly, an un-supervised K-means method is used for automatically estimating the cloud statistic of Formosat-2 image. Secondly, manual estimation of cloud coverage from Formosat-2 image is processed by manual examination. Apparently, a more accurate Automatic Cloud Coverage Assessment (ACCA) method certainly increases the efficiency of processing step 2 with a good prediction of cloud statistic. In this paper, mainly based on the research results from Chang et al, Irish, and Gotoh, we propose a modified Formosat-2 ACCA method which considered pre-processing and post-processing analysis. For pre-processing analysis, cloud statistic is determined by using un-supervised K-means classification, Sobel's method, Otsu's method, non-cloudy pixels reexamination, and cross-band filter method. Box-Counting fractal method is considered as a post-processing tool to double check the results of pre-processing analysis for increasing the efficiency of manual examination.

Identification of a Debris Cloud from the Nuclear Powered SNAPSHOT Satellite with Haystack Radar Measurements

NASA Technical Reports Server (NTRS)

Stokely, C.; Stansbery, E.

2006-01-01

Data from the MIT Lincoln Laboratory (MIT/LL) Long Range Imaging Radar (known as the Haystack radar) have been used in the past to examine families of objects from individual satellite breakups or families of orbiting objects that can be isolated in altitude and inclination. This is possible because for some time after a breakup, the debris cloud of particles can remain grouped together in similar orbit planes. This cloud will be visible to the radar, in fixed staring mode, for a short time twice each day, as the orbit plane moves through the field of view. There should be a unique three-dimensional pattern in observation time, range, and range rate which can identify the cloud. Eventually, through slightly differing precession rates of the right ascension of ascending node of the debris cloud, the observation time becomes distributed so that event identification becomes much more difficult. Analyses of the patterns in observation time, range, and range rate have identified good debris candidates released from the polar orbiting SNAPSHOT satellite (International Identifier: 1965-027A). For orbits near 90o inclination, there is essentially no precession of the orbit plane. The SNAPSHOT satellite is a well known nuclear powered satellite launched in 1965 to a near circular 1300 km orbit with an inclination of 90.3o. This satellite began releasing debris in 1979 with new pieces being discovered and cataloged over the years. 51 objects are still being tracked by the United States Space Surveillance Network. An analysis of the Haystack data has identified at least 60 pieces of debris separate from the 51 known tracked debris pieces, where all but 2 of the 60 pieces have a size less than 10cm. The altitude and inclination (derived from range-rate with a circular orbit assumption) are consistent with the SNAPSHOT satellite and its tracked debris cloud.

Jupiter Equatorial Region

NASA Image and Video Library

1998-03-06

This photographic mosaic of images from NASA's Galileo spacecraft covers an area of 34,000 kilometers by 22,000 kilometers (about 21,100 by 13,600 miles) in Jupiter's equatorial region. The dark region near the center of the mosaic is an equatorial "hotspot" similar to the site where the Galileo Probe parachuted into Jupiter's atmosphere in December 1995. These features are holes in the bright, reflective, equatorial cloud layer where heat from Jupiter's deep atmosphere can pass through. The circulation patterns observed here along with the composition measurements from the Galileo Probe suggest that dry air may be converging and sinking over these regions, maintaining their cloud-free appearance. The bright oval in the upper right of the mosaic as well as the other smaller bright features are examples of upwelling of moist air and condensation. These images were taken on December 17, 1996, at a range of 1.5 million kilometers (about 930,000 miles) by the Solid State Imaging camera system aboard Galileo. North is at the top. The mosaic covers latitudes 1 to 19 degrees and is centered at longitude 336 degrees west. The smallest resolved features are tens of kilometers in size. http://photojournal.jpl.nasa.gov/catalog/PIA00604

Tornado occurrences related to overshooting cloud-top heights as determined from ATS pictures

NASA Technical Reports Server (NTRS)

Fujita, T. T.

1972-01-01

A sequence of ATS 3 pictures including the development history of large anvil clouds near Salina, Kansas was enlarged by NASA into 8X negatives which were used to obtain the best quality prints by mixing scan lines in 8 steps to minimize checker-board patterns. These images resulted in the best possible resolution, permitting use to compute the heights of overshooting tops above environmental anvil levels based on cloud shadow relationships along with the techniques of lunar topographic mapping. Of 39 heights computed, 6 were within 15 miles of reported positions of 3 tornadoes. It was found that the tornado proximity tops were mostly less than 5000 ft, with one exception of 7000 ft, suggesting that tornadoes are most likely to occur when overshooting height decreases. In order to simulate surface vortices induced by cloud-scale rotation and updraft fields, a laboratory model was constructed. The model experiment has shown that the rotation or updraft field induces a surface vortex but their combination does prevent the formation of the surface vortex. This research leads to a conclusion that the determination of the cloud-top topography and its time variation is of extreme importance in predicting severe local storms for a period of 0 to 6 hours.

Multiple Scattering in Clouds: Insights from Three-Dimensional Diffusion/P{sub 1} Theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, Anthony B.; Marshak, Alexander

2001-03-15

In the atmosphere, multiple scattering matters nowhere more than in clouds, and being a product of its turbulence, clouds are highly variable environments. This challenges three-dimensional (3D) radiative transfer theory in a way that easily swamps any available computational resources. Fortunately, the far simpler diffusion (or P{sub 1}) theory becomes more accurate as the scattering intensifies, and allows for some analytical progress as well as computational efficiency. After surveying current approaches to 3D solar cloud-radiation problems from the diffusion standpoint, a general 3D result in steady-state diffusive transport is derived relating the variability-induced change in domain-average flux (i.e., diffuse transmittance)more » to the one-point covariance of internal fluctuations in particle density and in radiative flux. These flux variations follow specific spatial patterns in deliberately hydrodynamical language: radiative channeling. The P{sub 1} theory proves even more powerful when the photon diffusion process unfolds in time as well as space. For slab geometry, characteristic times and lengths that describe normal and transverse transport phenomena are derived. This phenomenology is used to (a) explain persistent features in satellite images of dense stratocumulus as radiative channeling, (b) set limits on current cloud remote-sensing techniques, and (c) propose new ones both active and passive.« less

New Insights on Hydro-Climate Feedback Processes over the Tropical Ocean from TRMM

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Wu, H. T.; Li, Xiaofan; Sui, C. H.

2002-01-01

In this paper, we study hydro-climate feedback processes over the tropical oceans, by examining the relationships among large scale circulation and Tropical Rainfall Measuring Mission Microwave Imager-Sea Surface Temperature (TMI-SST), and a range of TRMM rain products including rain rate, cloud liquid water, precipitable water, cloud types and areal coverage, and precipitation efficiency. Results show that for a warm event (1998), the 28C threshold of convective precipitation is quite well defined over the tropical oceans. However, for a cold event (1999), the SST threshold is less well defined, especially over the central and eastern Pacific cold tongue, where stratiform rain occurs at much lower than 28 C. Precipitation rates and cloud liquid water are found to be more closely related to the large scale vertical motion than to the underlying SST. While total columnar water vapor is more strongly dependent on SST. For a large domain, over the eastern Pacific, we find that the areal extent of the cloudy region tends to shrink as the SST increases. Examination of the relationship between cloud liquid water and rain rate suggests that the residence time of cloud liquid water tends to be shorter, associated with higher precipitation efficiency in a warmer climate. It is hypothesized that the reduction in cloudy area may be influenced both by the shift in large scale cloud patterns in response to changes in large scale forcings, and possible increase in the cloud liquid water conversion to rain water in a warmer environment. Results of numerical experiments with the Goddard cloud resolving model to test the hypothesis will be discussed.

A Cloudy Day on Mars

NASA Technical Reports Server (NTRS)

2002-01-01

(Released 23 April 2002) The Science This image, centered near 49.7 N and 43.0 W (317.0 E), displays splotchy water ice clouds that obscure the surface. Most of Mars was in a relatively clear period when this image was acquired, which is why many of the other THEMIS images acquired during the same period do not have obvious signs of atmospheric dust or water ice clouds. This image is far enough north to catch the edge of the north polar hood that develops during the northern winter. This is a cap of water ice and CO₂ ice clouds that form over the Martian north pole. Mars has a number of interesting atmospheric phenomena which THEMIS will be able to view in addition to water ice clouds, including dust devils, dust storms, and tracking atmospheric temperatures with the infrared camera. The Story Anyone who's been on an airplane in a storm knows how clouds on Earth can block the view below. The thin water ice clouds on Mars might make things slightly blurry, but at least we can still see the surface. While the surface features may not be as clear in this image, it's actually kind of fascinating to see clouds at work, because we can get a sense of how the north pole on Mars influences the weather and the climate. In this image, the north pole is responsible for the presence of the clouds. Made of water ice and carbon dioxide, these clouds 'mist out' in a atmospheric 'hood' that caps the surface during the northern Martian winter, hiding it from full view of eager observers here on Earth.

HUBBLE SHOWS EXPANSION OF ETA CARINAE DEBRIS

NASA Technical Reports Server (NTRS)

2002-01-01

The furious expansion of a huge, billowing pair of gas and dust clouds are captured in this NASA Hubble Space Telescope comparison image of the supermassive star Eta Carinae. To create the picture, astronomers aligned and subtracted two images of Eta Carinae taken 17 months apart (April 1994, September 1995). Black represents where the material was located in the older image, and white represents the more recent location. (The light and dark streaks that make an 'X' pattern are instrumental artifacts caused by the extreme brightness of the central star. The bright white region at the center of the image results from the star and its immediate surroundings being 'saturated' in one of the images.)Photo Credit: Jon Morse (University of Colorado), Kris Davidson (University of Minnesota), and NASA Image files in GIF and JPEG format and captions may be accessed on Internet via anonymous ftp from oposite.stsci.edu in /pubinfo.

Stereographic observations from geosynchronous satellites - An important new tool for the atmospheric sciences

NASA Technical Reports Server (NTRS)

Hasler, A. F.

1981-01-01

Observations of cloud geometry using scan-synchronized stereo geostationary satellites having images with horizontal spatial resolution of approximately 0.5 km, and temporal resolution of up to 3 min are presented. The stereo does not require a cloud with known emissivity to be in equilibrium with an atmosphere with a known vertical temperature profile. It is shown that absolute accuracies of about 0.5 km are possible. Qualitative and quantitative representations of atmospheric dynamics were shown by remapping, display, and stereo image analysis on an interactive computer/imaging system. Applications of stereo observations include: (1) cloud top height contours of severe thunderstorms and hurricanes, (2) cloud top and base height estimates for cloud-wind height assignment, (3) cloud growth measurements for severe thunderstorm over-shooting towers, (4) atmospheric temperature from stereo heights and infrared cloud top temperatures, and (5) cloud emissivity estimation. Recommendations are given for future improvements in stereo observations, including a third GOES satellite, operational scan synchronization of all GOES satellites and better resolution sensors.

A cloud-based multimodality case file for mobile devices.

PubMed

Balkman, Jason D; Loehfelm, Thomas W

2014-01-01

Recent improvements in Web and mobile technology, along with the widespread use of handheld devices in radiology education, provide unique opportunities for creating scalable, universally accessible, portable image-rich radiology case files. A cloud database and a Web-based application for radiologic images were developed to create a mobile case file with reasonable usability, download performance, and image quality for teaching purposes. A total of 75 radiology cases related to breast, thoracic, gastrointestinal, musculoskeletal, and neuroimaging subspecialties were included in the database. Breast imaging cases are the focus of this article, as they best demonstrate handheld display capabilities across a wide variety of modalities. This case subset also illustrates methods for adapting radiologic content to cloud platforms and mobile devices. Readers will gain practical knowledge about storage and retrieval of cloud-based imaging data, an awareness of techniques used to adapt scrollable and high-resolution imaging content for the Web, and an appreciation for optimizing images for handheld devices. The evaluation of this software demonstrates the feasibility of adapting images from most imaging modalities to mobile devices, even in cases of full-field digital mammograms, where high resolution is required to represent subtle pathologic features. The cloud platform allows cases to be added and modified in real time by using only a standard Web browser with no application-specific software. Challenges remain in developing efficient ways to generate, modify, and upload radiologic and supplementary teaching content to this cloud-based platform. Online supplemental material is available for this article. ©RSNA, 2014.

GIFT-Cloud: A data sharing and collaboration platform for medical imaging research.

PubMed

Doel, Tom; Shakir, Dzhoshkun I; Pratt, Rosalind; Aertsen, Michael; Moggridge, James; Bellon, Erwin; David, Anna L; Deprest, Jan; Vercauteren, Tom; Ourselin, Sébastien

2017-02-01

Clinical imaging data are essential for developing research software for computer-aided diagnosis, treatment planning and image-guided surgery, yet existing systems are poorly suited for data sharing between healthcare and academia: research systems rarely provide an integrated approach for data exchange with clinicians; hospital systems are focused towards clinical patient care with limited access for external researchers; and safe haven environments are not well suited to algorithm development. We have established GIFT-Cloud, a data and medical image sharing platform, to meet the needs of GIFT-Surg, an international research collaboration that is developing novel imaging methods for fetal surgery. GIFT-Cloud also has general applicability to other areas of imaging research. GIFT-Cloud builds upon well-established cross-platform technologies. The Server provides secure anonymised data storage, direct web-based data access and a REST API for integrating external software. The Uploader provides automated on-site anonymisation, encryption and data upload. Gateways provide a seamless process for uploading medical data from clinical systems to the research server. GIFT-Cloud has been implemented in a multi-centre study for fetal medicine research. We present a case study of placental segmentation for pre-operative surgical planning, showing how GIFT-Cloud underpins the research and integrates with the clinical workflow. GIFT-Cloud simplifies the transfer of imaging data from clinical to research institutions, facilitating the development and validation of medical research software and the sharing of results back to the clinical partners. GIFT-Cloud supports collaboration between multiple healthcare and research institutions while satisfying the demands of patient confidentiality, data security and data ownership. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Content-based histopathology image retrieval using CometCloud.

PubMed

Qi, Xin; Wang, Daihou; Rodero, Ivan; Diaz-Montes, Javier; Gensure, Rebekah H; Xing, Fuyong; Zhong, Hua; Goodell, Lauri; Parashar, Manish; Foran, David J; Yang, Lin

2014-08-26

The development of digital imaging technology is creating extraordinary levels of accuracy that provide support for improved reliability in different aspects of the image analysis, such as content-based image retrieval, image segmentation, and classification. This has dramatically increased the volume and rate at which data are generated. Together these facts make querying and sharing non-trivial and render centralized solutions unfeasible. Moreover, in many cases this data is often distributed and must be shared across multiple institutions requiring decentralized solutions. In this context, a new generation of data/information driven applications must be developed to take advantage of the national advanced cyber-infrastructure (ACI) which enable investigators to seamlessly and securely interact with information/data which is distributed across geographically disparate resources. This paper presents the development and evaluation of a novel content-based image retrieval (CBIR) framework. The methods were tested extensively using both peripheral blood smears and renal glomeruli specimens. The datasets and performance were evaluated by two pathologists to determine the concordance. The CBIR algorithms that were developed can reliably retrieve the candidate image patches exhibiting intensity and morphological characteristics that are most similar to a given query image. The methods described in this paper are able to reliably discriminate among subtle staining differences and spatial pattern distributions. By integrating a newly developed dual-similarity relevance feedback module into the CBIR framework, the CBIR results were improved substantially. By aggregating the computational power of high performance computing (HPC) and cloud resources, we demonstrated that the method can be successfully executed in minutes on the Cloud compared to weeks using standard computers. In this paper, we present a set of newly developed CBIR algorithms and validate them using two different pathology applications, which are regularly evaluated in the practice of pathology. Comparative experimental results demonstrate excellent performance throughout the course of a set of systematic studies. Additionally, we present and evaluate a framework to enable the execution of these algorithms across distributed resources. We show how parallel searching of content-wise similar images in the dataset significantly reduces the overall computational time to ensure the practical utility of the proposed CBIR algorithms.

Tropical Cyclone Monty Strikes Western Australia

NASA Technical Reports Server (NTRS)

2004-01-01

The Multi-angle Imaging SpectroRadiometer (MISR) acquired these natural color images and cloud top height measurements for Monty before and after the storm made landfall over the remote Pilbara region of Western Australia, on February 29 and March 2, 2004 (shown as the left and right-hand image sets, respectively). On February 29, Monty was upgraded to category 4 cyclone status. After traveling inland about 300 kilometers to the south, the cyclonic circulation had decayed considerably, although category 3 force winds were reported on the ground. Some parts of the drought-affected Pilbara region received more than 300 millimeters of rainfall, and serious and extensive flooding has occurred.

The natural color images cover much of the same area, although the right-hand panels are offset slightly to the east. Automated stereoscopic processing of data from multiple MISR cameras was utilized to produce the cloud-top height fields. The distinctive spatial patterns of the clouds provide the necessary contrast to enable automated feature matching between images acquired at different view angles. The height retrievals are at this stage uncorrected for the effects of the high winds associated with cyclone rotation. Areas where heights could not be retrieved are shown in dark gray.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbits 22335 and 22364. The panels cover an area of about 380 kilometers x 985 kilometers, and utilize data from blocks 105 to 111 within World Reference System-2 paths 115 and 113.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Earth Observations taken by the Expedition 13 crew

NASA Image and Video Library

2006-05-27

ISS013-E-27590 (27 May 2006) --- Aves Island, Caribbean Sea is featured in this image photographed by an Expedition 13 crewmember on the International Space Station. This image is a rare almost cloud free view of the island and the submerged fringing coral reef that surrounds it. Scientists believe the crosshatch-like pattern of roughness on the surrounding sea surface was caused by variable winds at the time of image acquisition. The island itself currently stands a mere 4 meters above the surrounding sea surface, and in high seas it can be completely submerged. While the low elevation of the island makes it a hazard to shipping, it also provides a major nesting site for green sea turtles (Chelonia mydas) in the Caribbean.

Coupled Retrieval of Liquid Water Cloud and Above-Cloud Aerosol Properties Using the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)

NASA Astrophysics Data System (ADS)

Xu, Feng; van Harten, Gerard; Diner, David J.; Davis, Anthony B.; Seidel, Felix C.; Rheingans, Brian; Tosca, Mika; Alexandrov, Mikhail D.; Cairns, Brian; Ferrare, Richard A.; Burton, Sharon P.; Fenn, Marta A.; Hostetler, Chris A.; Wood, Robert; Redemann, Jens

2018-03-01

An optimization algorithm is developed to retrieve liquid water cloud properties including cloud optical depth (COD), droplet size distribution and cloud top height (CTH), and above-cloud aerosol properties including aerosol optical depth (AOD), single-scattering albedo, and microphysical properties from sweep-mode observations by Jet Propulsion Laboratory's Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) instrument. The retrieval is composed of three major steps: (1) initial estimate of the mean droplet size distribution across the entire image of 80-100 km along track by 10-25 km across track from polarimetric cloudbow observations, (2) coupled retrieval of image-scale cloud and above-cloud aerosol properties by fitting the polarimetric data at all observation angles, and (3) iterative retrieval of 1-D radiative transfer-based COD and droplet size distribution at pixel scale (25 m) by establishing relationships between COD and droplet size and fitting the total radiance measurements. Our retrieval is tested using 134 AirMSPI data sets acquired during the National Aeronautics and Space Administration (NASA) field campaign ObseRvations of Aerosols above CLouds and their intEractionS. The retrieved above-cloud AOD and CTH are compared to coincident HSRL-2 (HSRL-2, NASA Langley Research Center) data, and COD and droplet size distribution parameters (effective radius reff and effective variance veff) are compared to coincident Research Scanning Polarimeter (RSP) (NASA Goddard Institute for Space Studies) data. Mean absolute differences between AirMSPI and HSRL-2 retrievals of above-cloud AOD at 532 nm and CTH are 0.03 and <0.5 km, respectively. At RSP's footprint scale ( 323 m), mean absolute differences between RSP and AirMSPI retrievals of COD, reff, and veff in the cloudbow area are 2.33, 0.69 μm, and 0.020, respectively. Neglect of smoke aerosols above cloud leads to an underestimate of image-averaged COD by 15%.

Measurement of optical blurring in a turbulent cloud chamber

NASA Astrophysics Data System (ADS)

Packard, Corey D.; Ciochetto, David S.; Cantrell, Will H.; Roggemann, Michael C.; Shaw, Raymond A.

2016-10-01

Earth's atmosphere can significantly impact the propagation of electromagnetic radiation, degrading the performance of imaging systems. Deleterious effects of the atmosphere include turbulence, absorption and scattering by particulates. Turbulence leads to blurring, while absorption attenuates the energy that reaches imaging sensors. The optical properties of aerosols and clouds also impact radiation propagation via scattering, resulting in decorrelation from unscattered light. Models have been proposed for calculating a point spread function (PSF) for aerosol scattering, providing a method for simulating the contrast and spatial detail expected when imaging through atmospheres with significant aerosol optical depth. However, these synthetic images and their predicating theory would benefit from comparison with measurements in a controlled environment. Recently, Michigan Technological University (MTU) has designed a novel laboratory cloud chamber. This multiphase, turbulent "Pi Chamber" is capable of pressures down to 100 hPa and temperatures from -55 to +55°C. Additionally, humidity and aerosol concentrations are controllable. These boundary conditions can be combined to form and sustain clouds in an instrumented laboratory setting for measuring the impact of clouds on radiation propagation. This paper describes an experiment to generate mixing and expansion clouds in supersaturated conditions with salt aerosols, and an example of measured imagery viewed through the generated cloud is shown. Aerosol and cloud droplet distributions measured during the experiment are used to predict scattering PSF and MTF curves, and a methodology for validating existing theory is detailed. Measured atmospheric inputs will be used to simulate aerosol-induced image degradation for comparison with measured imagery taken through actual cloud conditions. The aerosol MTF will be experimentally calculated and compared to theoretical expressions. The key result of this study is the proposal of a closure experiment for verification of theoretical aerosol effects using actual clouds in a controlled laboratory setting.

CEDIMS: cloud ethical DICOM image Mojette storage

NASA Astrophysics Data System (ADS)

Guédon, Jeanpierre; Evenou, Pierre; Tervé, Pierre; David, Sylvain; Béranger, Jérome

2012-02-01

Dicom images of patients will necessarily been stored in Clouds. However, ethical constraints must apply. In this paper, a method which provides the two following conditions is presented: 1) the medical information is not readable by the cloud owner since it is distributed along several clouds 2) the medical information can be retrieved from any sufficient subset of clouds In order to obtain this result in a real time processing, the Mojette transform is used. This paper reviews the interesting features of the Mojette transform in terms of information theory. Since only portions of the original Dicom files are stored into each cloud, their contents are not reachable. For instance, we use 4 different public clouds to save 4 different projections of each file, with the additional condition that any 3 over 4 projections are enough to reconstruct the original file. Thus, even if a cloud is unavailable when the user wants to load a Dicom file, the other 3 are giving enough information for real time reconstruction. The paper presents an implementation on 3 actual clouds. For ethical reasons, we use a Dicom image spreaded over 3 public clouds to show the obtained confidentiality and possible real time recovery.

HUBBLE FINDS MANY BRIGHT CLOUDS ON URANUS

NASA Technical Reports Server (NTRS)

2002-01-01

A recent Hubble Space Telescope view reveals Uranus surrounded by its four major rings and by 10 of its 17 known satellites. This false-color image was generated by Erich Karkoschka using data taken on August 8, 1998, with Hubble's Near Infrared Camera and Multi-Object Spectrometer. Hubble recently found about 20 clouds - nearly as many clouds on Uranus as the previous total in the history of modern observations. The orange-colored clouds near the prominent bright band circle the planet at more than 300 mph (500 km/h), according to team member Heidi Hammel (MIT). One of the clouds on the right-hand side is brighter than any other cloud ever seen on Uranus. The colors in the image indicate altitude. Team member Mark Marley (New Mexico State University) reports that green and blue regions show where the atmosphere is clear and sunlight can penetrate deep into Uranus. In yellow and grey regions the sunlight reflects from a higher haze or cloud layer. Orange and red colors indicate very high clouds, such as cirrus clouds on Earth. The Hubble image is one of the first images revealing the precession of the brightest ring with respect to a previous image [LINK to PRC97-36a]. Precession makes the fainter part of the ring (currently on the upper right-hand side) slide around Uranus once every nine months. The fading is caused by ring particles crowding and hiding each other on one side of their eight-hour orbit around Uranus. The blue, green and red components of this false-color image correspond to exposures taken at near-infrared wavelengths of 0.9, 1.1, and 1.7 micrometers. Thus, regions on Uranus appearing blue, for example, reflect more sunlight at 0.9 micrometer than at the longer wavelengths. Apparent colors on Uranus are caused by absorption of methane gas in its atmosphere, an effect comparable to absorption in our atmosphere which can make distant clouds appear red. Credit: Erich Karkoschka (University of Arizona) and NASA

iss031e116058

NASA Image and Video Library

2012-06-13

ISS031-E-116058 (13 June 2012) --- Polar mesospheric clouds in the Northern Hemisphere are featured in this image photographed by an Expedition 31 crew member on the International Space Station. In both the Northern and Southern Hemisphere, during their respective late spring and early summer seasons, polar mesospheric clouds are at the peak of their visibility. Visible from the ground during twilight, aircraft in flight, and the International Space Station, they typically appear as delicate shining threads against the darkness of space?hence their other name of noctilucent or ?night-shining? clouds. On the same day this image was taken from the space station while it was passing over the night-darkened Tibetan Plateau, polar mesospheric clouds were also visible to aircraft flying above Canada. In addition to this still image, the space station crew took a time-lapse image sequence of polar mesospheric clouds several days earlier (June 5, 2012) while passing over western Asia; this is first such sequence of images of the phenomena taken from orbit. Polar mesospheric clouds form between 76-85 kilometers above the Earth?s surface, when there is sufficient water vapor at these high altitudes to freeze into ice crystals. The clouds are illuminated by the setting sun while the ground surface below is in darkness, lending them their night-shining properties. In addition to the illuminated tracery of polar mesospheric clouds trending across the center of the image, lower layers of the atmosphere are also illuminated; the lowest layer of the atmosphere, the stratosphere, is indicated by dim orange and red tones. While the exact cause of formation of polar mesospheric clouds is still debated?dust from meteors, global warming, and rocket exhaust have all been suggested as contributing factors?recent research suggests that changes in atmospheric gas composition or temperature has caused the clouds to become brighter over time.

New optical package and algorithms for accurate estimation and interactive recording of the cloud cover information over land and sea

NASA Astrophysics Data System (ADS)

Krinitskiy, Mikhail; Sinitsyn, Alexey; Gulev, Sergey

2014-05-01

Cloud fraction is a critical parameter for the accurate estimation of short-wave and long-wave radiation - one of the most important surface fluxes over sea and land. Massive estimates of the total cloud cover as well as cloud amount for different layers of clouds are available from visual observations, satellite measurements and reanalyses. However, these data are subject of different uncertainties and need continuous validation against highly accurate in-situ measurements. Sky imaging with high resolution fish eye camera provides an excellent opportunity for collecting cloud cover data supplemented with additional characteristics hardly available from routine visual observations (e.g. structure of cloud cover under broken cloud conditions, parameters of distribution of cloud dimensions). We present operational automatic observational package which is based on fish eye camera taking sky images with high resolution (up to 1Hz) in time and a spatial resolution of 968x648px. This spatial resolution has been justified as an optimal by several sensitivity experiments. For the use of the package at research vessel when the horizontal positioning becomes critical, a special extension of the hardware and software to the package has been developed. These modules provide the explicit detection of the optimal moment for shooting. For the post processing of sky images we developed a software realizing the algorithm of the filtering of sunburn effect in case of small and moderate could cover and broken cloud conditions. The same algorithm accurately quantifies the cloud fraction by analyzing color mixture for each point and introducing the so-called "grayness rate index" for every pixel. The accuracy of the algorithm has been tested using the data collected during several campaigns in 2005-2011 in the North Atlantic Ocean. The collection of images included more than 3000 images for different cloud conditions supplied with observations of standard parameters. The system is fully autonomous and has a block for digital data collection at the hard disk. The system has been tested for a wide range of open ocean cloud conditions and we will demonstrate some pilot results of data processing and physical interpretation of fractional cloud cover estimation.

KSC00vafbdig003

NASA Image and Video Library

2000-06-27

A crated National Oceanic and Atmospheric Administration (NOAA-L) satellite is moved inside the B16-10 spacecraft processing hangar at Vandenberg Air Force Base, Calif. NOAA-L is part of the Polar-Orbiting Operational Environmental Satellite (POES) program that provides atmospheric measurements of temperature, humidity, ozone and cloud images, tracking weather patterns that affect the global weather and climate. The launch of the NOAA-L satellite is scheduled no earlier than Sept. 12 aboard a Lockheed Martin Titan II rocket

KSC00vafbdig004

NASA Image and Video Library

2000-06-27

Inside the B16-10 spacecraft processing hangar at Vandenberg Air Force Base, Calif., workers oversee the uncrating of the National Oceanic and Atmospheric Administration (NOAA-L) satellite. NOAA-L is part of the Polar-Orbiting Operational Environmental Satellite (POES) program that provides atmospheric measurements of temperature, humidity, ozone and cloud images, tracking weather patterns that affect the global weather and climate. The launch of the NOAA-L satellite is scheduled no earlier than Sept. 12 aboard a Lockheed Martin Titan II rocket

Study of Aerosol - Cloud Interaction over Indo - Gangetic Basin During Normal Monsoon and Drought Years

NASA Astrophysics Data System (ADS)

Tiwari, S.; Ramachandran, S.

2017-12-01

Clouds are one of the major factors that influence the Earth's radiation budget and also change the precipitation pattern. Atmospheric aerosols play a crucial role in modifying the cloud properties acting as cloud condensation nuclei (CCN). It can change cloud droplet number concentration, cloud droplet size and hence cloud albedo. Therefore, the effects of aerosol on cloud parameters are one of the most important topics in climate change study. In the present study, we investigate the spatial variability of aerosol - cloud interactions during normal monsoon years and drought years over entire Indo - Gangetic Basin (IGB) which is one of the most polluted regions of the world. Based on aerosol loading and their major emission sources, we divided the entire IGB in to six major sub regions (R1: 66 - 71 E, 24 - 29 N; R2: 71 - 76 E, 29 - 34 N; R3: 76 - 81 E, 26 - 31 N; R4: 81 - 86 E, 23 - 28 N; R5: 86 - 91 E, 22 - 27 N and R6: 91 - 96 E, 23 - 28 N). With this objective, fifteen years (2001 - 2015), daily mean aerosol optical depth, cloud parameters and rainfall data obtained from MODerate resolution Imaging Spectroradiometer (MODIS) on board of Terra satellite and Tropical Rainfall Measuring Mission (TRMM) is analyzed over each sub regions of IGB for monsoon season (JJAS : June, July, August and September months). Preliminary results suggest that a slightly change in aerosol optical depth can affect the significant contribution of cloud fraction and other cloud properties which also show a large spatial heterogeneity. During drought years, higher cloud effective radius (i.e. CER > 20µm) decreases from western to eastern IGB suggesting the enhancement in cloud albedo. Relatively week correlation between cloud optical thickness and rainfall is found during drought years than the normal monsoon years over western IGB. The results from the present study will be helpful to reduce uncertainty in understanding of aerosol - cloud interaction over IGB. Further details will be presented during the conference.

Measuring cloud thermodynamic phase with shortwave infrared imaging spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, David R.; McCubbin, Ian; Gao, Bo Cai

Shortwave Infrared imaging spectroscopy enables accurate remote mapping of cloud thermodynamic phase at high spatial resolution. We describe a measurement strategy to exploit signatures of liquid and ice absorption in cloud top apparent reflectance spectra from 1.4 to 1.8 μm. This signal is generally insensitive to confounding factors such as solar angles, view angles, and surface albedo. We first evaluate the approach in simulation and then apply it to airborne data acquired in the Calwater-2/ACAPEX campaign of Winter 2015. Here NASA’s “Classic” Airborne Visible Infrared Imaging Spectrometer (AVIRIS-C) remotely observed diverse cloud formations while the U.S. Department of Energy ARMmore » Aerial Facility G-1 aircraft measured cloud integral and microphysical properties in situ. Finally, the coincident measurements demonstrate good separation of the thermodynamic phases for relatively homogeneous clouds.« less

ARC-1990-A91-2001

NASA Image and Video Library

1990-02-19

Range : 60,000 miles These images are two versions of a near-infrafed map of lower-level clouds on the night side of Venus, obtained by the Near Infrared Mapping Spectrometer aboard the Galileo spacecraft.The map shows the turbulent, cloudy middle atmosphere some 30-33 miles above the surface, 6-10 miles below the visible cloudtops. The image to the left shows the radiant heat from the lower atmosphere (about 400 degrees F) ahining through the sulfuric acid clouds, which appear as much as 10 times darker than the bright gaps between clouds. This cloud layer is at about 170 degrees F, at a pressure about 1/2 Earth's atmospheric pressure. About 2/3 of the dark hemisphere is visible, centered on longitude 350 West, with bright slsivers of daylit high clouds visible at top and bottom left. The right image, a modified negative, represents what scientists believe would be the visual appearance of this mid-level cloud deck in daylight, with the clouds reflecting sunlight instead of clocking out infrared from the hot planet and lower atmosphere. Near the equator, the clouds appear fluffy and clocky; farther north, they are stretched out into East-West filaments by winds estimated at more than 150 mph, while the poles are capped by thick clouds at this altitude. The Near Infrared Mapping Spectrometer (NIMS) on the Galileo is a combined mapping (imaging) and spectral instrument. It can sense 408 contiguous wavelengths from 0.7 microns (deep red) to 5.2 microns, and can construct a map or image by mechanical scanning. It can spectroscopic-ally analyze atmospheres and surfaces and construct thermal and chemical maps.

ARC-1990-A91-2002

NASA Image and Video Library

1990-02-10

Range : 60,000 miles These images are two versions of a near-infrafed map of lower-level clouds on the night side of Venus, obtained by the Near Infrared Mapping Spectrometer aboard the Galileo spacecraft.The map shows the turbulent, cloudy middle atmosphere some 30-33 miles above the surface, 6-10 miles below the visible cloudtops. The image to the left shows the radiant heat from the lower atmosphere (about 400 degrees F) ahining through the sulfuric acid clouds, which appear as much as 10 times darker than the bright gaps between clouds. This cloud layer is at about 170 degrees F, at a pressure about 1/2 Earth's atmospheric pressure. About 2/3 of the dark hemisphere is visible, centered on longitude 350 West, with bright slsivers of daylit high clouds visible at top and bottom left. The right image, a modified negative, represents what scientists believe would be the visual appearance of this mid-level cloud deck in daylight, with the clouds reflecting sunlight instead of clocking out infrared from the hot planet and lower atmosphere. Near the equator, the clouds appear fluffy and clocky; farther north, they are stretched out into East-West filaments by winds estimated at more than 150 mph, while the poles are capped by thick clouds at this altitude. The Near Infrared Mapping Spectrometer (NIMS) on the Galileo is a combined mapping (imaging) and spectral instrument. It can sense 408 contiguous wavelengths from 0.7 microns (deep red) to 5.2 microns, and can construct a map or image by mechanical scanning. It can spectroscopic-ally analyze atmospheres and surfaces and construct thermal and chemical maps.

Coastal Fog, South Peruvian Coast at Pisco

NASA Technical Reports Server (NTRS)

2002-01-01

Coastal fog commonly drapes the Peruvian coast. This image captures complex interactions between land, sea, and atmosphere along the southern Peruvian coast. When Shuttle astronauts took the image in February of 2002, the layers of coastal fog and stratus were being progressively scoured away by brisk south to southeast winds. Remnants of the cloud deck banked against the larger, obstructing headlands like Peninsula Paracas and Isla Sangayan, giving the prominent 'white comma' effect. Southerlies also produced ripples of internal gravity waves in the clouds offshore where warm, dry air aloft interacts with a thinning layer of cool, moist air near the sea surface on the outer edge of the remaining cloud bank. South of Peninsula Baracas, the small headlands channeled the clouds into streaks-local horizontal vortices caused by the headlands provided enough lift to give points of origin of the clouds in some bays. Besides the shelter of the peninsula, the Bahia de Pisco appears to be cloud-free due to a dry, offshore flow down the valley of the Rio Ica. The STS-109 crew took image STS109-730-80 in February 2002. The image is provided by the Earth Sciences and Image Analysis Laboratory at Johnson Space Center. Additional images taken by astronauts and cosmonauts can be viewed at the NASA-JSC Gateway to Astronaut Photography of Earth.

E4 True and false color hot spot mosaic

NASA Technical Reports Server (NTRS)

1997-01-01

True and false color views of Jupiter from NASA's Galileo spacecraft show an equatorial 'hotspot' on Jupiter. These images cover an area 34,000 kilometers by 11,000 kilometers (about 21,100 by 6,800 miles). The top mosaic combines the violet and near infrared continuum filter images to create an image similar to how Jupiter would appear to human eyes. Differences in coloration are due to the composition and abundances of trace chemicals in Jupiter's atmosphere. The bottom mosaic uses Galileo's three near-infrared wavelengths displayed in red, green, and blue) to show variations in cloud height and thickness. Bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the deep cloud with an overlying thin haze. The light blue region to the left is covered by a very high haze layer. The multicolored region to the right has overlapping cloud layers of different heights. Galileo is the first spacecraft to distinguish cloud layers on Jupiter.

North is at the top. The mosaic covers latitudes 1 to 10 degrees and is centered at longitude 336 degrees west. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers (about 930,000 miles) by the Solid State Imaging camera system aboard Galileo. The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at: http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at: http:/ /www.jpl.nasa.gov/galileo/sepo.

Titan Lingering Clouds

NASA Image and Video Library

2009-06-03

Lots of clouds are visible in this infrared image of Saturn's moon Titan. These clouds form and move much like those on Earth, but in a much slower, more lingering fashion, new results from NASA's Cassini spacecraft show. Scientists have monitored Titan's atmosphere for three-and-a-half years, between July 2004 and December 2007, and observed more than 200 clouds. The way these clouds are distributed around Titan matches scientists' global circulation models. The only exception is timing—clouds are still noticeable in the southern hemisphere while fall is approaching. Three false-color images make up this mosaic and show the clouds at 40 to 50 degrees mid-latitude. The images were taken by Cassini's visual and infrared mapping spectrometer during a close flyby of Titan on Sept. 7, 2006, known as T17. For a similar view see PIA12005. Each image is a color composite, with red shown at the 2-micron wavelength, green at 1.6 microns, and blue at 2.8 microns. An infrared color mosaic is also used as a background (red at 5 microns, green at 2 microns and blue at 1.3 microns). The characteristic elongated mid-latitude clouds, which are easily visible in bright bluish tones are still active even late into 2006-2007. According to climate models, these clouds should have faded out since 2005. http://photojournal.jpl.nasa.gov/catalog/PIA12004

Preparation of Ultracold Atom Clouds at the Shot Noise Level.

PubMed

Gajdacz, M; Hilliard, A J; Kristensen, M A; Pedersen, P L; Klempt, C; Arlt, J J; Sherson, J F

2016-08-12

We prepare number stabilized ultracold atom clouds through the real-time analysis of nondestructive images and the application of feedback. In our experiments, the atom number N∼10^{6} is determined by high precision Faraday imaging with uncertainty ΔN below the shot noise level, i.e., ΔN

Titan South Polar Cloud Burst

NASA Image and Video Library

2009-06-03

This infrared image of Saturn's moon Titan shows a large burst of clouds in the moon's south polar region. These clouds form and move much like those on Earth, but in a much slower, more lingering fashion, new results from NASA's Cassini Spacecraft show. This image is a color composite, with red shown at a 5-micron wavelength, green at 2.7 microns, and blue at 2 microns. An infrared color mosaic is also used as a background image (red at 5 microns, green at 2 microns, blue at 1.3 microns). The images were taken by Cassini's visual and infrared mapping spectrometer during a flyby of Titan on March 26, 2007, known as T27. For a similar view see PIA12004. Titan's southern hemisphere still shows a very active meteorology (the cloud appears in white-reddish tones) even in 2007. According to climate models, these clouds should have faded out since 2005. Scientists have monitored Titan's atmosphere for three-and-a-half years, between July 2004 and December 2007, and observed more than 200 clouds. The way these clouds are distributed around Titan matches scientists' global circulation models. The only exception is timing—clouds are still noticeable in the southern hemisphere while fall is approaching. http://photojournal.jpl.nasa.gov/catalog/PIA12005

Long-term Behaviour Of Venus Winds At Cloud Level From Virtis/vex Observations

NASA Astrophysics Data System (ADS)

Hueso, Ricardo; Peralta, J.; Sánchez-Lavega, A.; Pérez-Hoyos, S.; Piccioni, G.; Drossart, P.

2009-09-01

The Venus Express (VEX) mission has been in orbit to Venus for more than three years now. The VIRTIS instrument onboard VEX observes Venus in two channels (visible and infrared) obtaining spectra and multi-wavelength images of the planet. Images in the ultraviolet range are used to study the upper cloud at 66 km while images in the infrared (1.74 μm) map the opacity of the lower cloud deck at 48 km. Here we present an analysis of the overall dynamics of Venus’ atmosphere at both levels using observations that cover a large fraction of the VIRTIS dataset. We will present our latest results concerning the zonal winds, the overall stability in the lower cloud deck motions and the variability in the upper cloud. Meridional winds are also observed in the upper and lower cloud in the UV and IR images obtained with VIRTIS. While the upper clouds present a net meridional motion consistent with the upper branch of a Hadley cell the lower cloud present more irregular, variable and less intense motions in the meridional direction. Acknowledgements This work has been funded by Spanish MEC AYA2006-07735 with FEDER support and Grupos Gobierno Vasco IT-464-07. RH acknowledges a "Ramón y Cajal” contract from MEC.

Multilayered Clouds Identification and Retrieval for CERES Using MODIS

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Yi, Yuhong; Huang, Jainping; Lin, Bin; Fan, Alice; Gibson, Sharon; Chang, Fu-Lung

2006-01-01

Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on Aqua, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to MODIS and AMSR-E data taken from the Aqua satellite over non-polar ocean surfaces.

Tropical Depression Debbie in the Atlantic

NASA Image and Video Library

2006-08-22

These images show Tropical Depression Debbie in the Atlantic, from the Atmospheric Infrared Sounder (AIRS) on NASA's Aqua satellite on August 22, 2006. This AIRS image shows the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures (in purple) are associated with high, cold cloud tops that make up the top of the storm. The infrared signal does not penetrate through clouds. Where there are no clouds the AIRS instrument reads the infrared signal from the surface of the Earth, revealing warmer temperatures (red). At the time the data were taken from which these images were made the eye had not yet opened but the storm is now well organized. The location of the future eye appears as a circle at 275 K brightness temperature in the microwave image just to the SE of the Azores. http://photojournal.jpl.nasa.gov/catalog/PIA00508

New Satellite Estimates of Mixed-Phase Cloud Properties: A Synergistic Approach for Application to Global Satellite Imager Data

NASA Astrophysics Data System (ADS)

Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.

2016-12-01

Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and validated with icing PIREPS. The initial validation is encouraging for single-layer cloud conditions. More work is needed to test and refine the method for global application in a wider range of cloud conditions. A brief overview of our current method, applications, verification, and plans for future work will be presented.

Oblique view of cloud patterns over Pacific Ocean

NASA Image and Video Library

1975-07-16

AST-01-042 (16 July 1975) --- An oblique view of unique cloud patterns over the Pacific Ocean caused by aircraft contrail shadows altering cumulus clouds and forming straight line clouds, as photographed from the Apollo spacecraft in Earth orbit during the joint U.S.-USSR Apollo-Soyuz Test Project mission. This area is southwest of Los Angeles, California. This photograph was taken at an altitude of 177 kilometers (110 statute miles) with a 70mm Hasselblad camera using medium-speed Ektachrome QX-807 type film.

The EOS CERES Global Cloud Mask

NASA Technical Reports Server (NTRS)

Berendes, T. A.; Welch, R. M.; Trepte, Q.; Schaaf, C.; Baum, B. A.

1996-01-01

To detect long-term climate trends, it is essential to produce long-term and consistent data sets from a variety of different satellite platforms. With current global cloud climatology data sets, such as the International Satellite Cloud Climatology Experiment (ISCCP) or CLAVR (Clouds from Advanced Very High Resolution Radiometer), one of the first processing steps is to determine whether an imager pixel is obstructed between the satellite and the surface, i.e., determine a cloud 'mask.' A cloud mask is essential to studies monitoring changes over ocean, land, or snow-covered surfaces. As part of the Earth Observing System (EOS) program, a series of platforms will be flown beginning in 1997 with the Tropical Rainfall Measurement Mission (TRMM) and subsequently the EOS-AM and EOS-PM platforms in following years. The cloud imager on TRMM is the Visible/Infrared Sensor (VIRS), while the Moderate Resolution Imaging Spectroradiometer (MODIS) is the imager on the EOS platforms. To be useful for long term studies, a cloud masking algorithm should produce consistent results between existing (AVHRR) data, and future VIRS and MODIS data. The present work outlines both existing and proposed approaches to detecting cloud using multispectral narrowband radiance data. Clouds generally are characterized by higher albedos and lower temperatures than the underlying surface. However, there are numerous conditions when this characterization is inappropriate, most notably over snow and ice of the cloud types, cirrus, stratocumulus and cumulus are the most difficult to detect. Other problems arise when analyzing data from sun-glint areas over oceans or lakes over deserts or over regions containing numerous fires and smoke. The cloud mask effort builds upon operational experience of several groups that will now be discussed.

Deep Clouds

NASA Image and Video Library

2008-05-27

Bright puffs and ribbons of cloud drift lazily through Saturn's murky skies. In contrast to the bold red, orange and white clouds of Jupiter, Saturn's clouds are overlain by a thick layer of haze. The visible cloud tops on Saturn are deeper in its atmosphere due to the planet's cooler temperatures. This view looks toward the unilluminated side of the rings from about 18 degrees above the ringplane. Images taken using red, green and blue spectral filters were combined to create this natural color view. The images were acquired with the Cassini spacecraft wide-angle camera on April 15, 2008 at a distance of approximately 1.5 million kilometers (906,000 miles) from Saturn. Image scale is 84 kilometers (52 miles) per pixel. http://photojournal.jpl.nasa.gov/catalog/PIA09910

Remote Sensing of Water Vapor and Thin Cirrus Clouds using MODIS Near-IR Channels

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Kaufman, Yoram J.

2001-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major facility instrument on board the Terra Spacecraft, was successfully launched into space in December of 1999. MODIS has several near-IR channels within and around the 0.94 micrometer water vapor bands for remote sensing of integrated atmospheric water vapor over land and above clouds. MODIS also has a special near-IR channel centered at 1.375-micron with a width of 30 nm for remote sensing of cirrus clouds. In this paper, we describe briefly the physical principles on remote sensing of water vapor and cirrus clouds using these channels. We also present sample water vapor images and cirrus cloud images obtained from MODIS data.

An assessment of thin cloud detection by applying bidirectional reflectance distribution function model-based background surface reflectance using Geostationary Ocean Color Imager (GOCI): A case study for South Korea

NASA Astrophysics Data System (ADS)

Kim, Hye-Won; Yeom, Jong-Min; Shin, Daegeun; Choi, Sungwon; Han, Kyung-Soo; Roujean, Jean-Louis

2017-08-01

In this study, a new assessment of thin cloud detection with the application of bidirectional reflectance distribution function (BRDF) model-based background surface reflectance was undertaken by interpreting surface spectra characterized using the Geostationary Ocean Color Imager (GOCI) over a land surface area. Unlike cloud detection over the ocean, the detection of cloud over land surfaces is difficult due to the complicated surface scattering characteristics, which vary among land surface types. Furthermore, in the case of thin clouds, in which the surface and cloud radiation are mixed, it is difficult to detect the clouds in both land and atmospheric fields. Therefore, to interpret background surface reflectance, especially underneath cloud, the semiempirical BRDF model was used to simulate surface reflectance by reflecting solar angle-dependent geostationary sensor geometry. For quantitative validation, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data were used to make a comparison with the proposed cloud masking result. As a result, the new cloud masking scheme resulted in a high probability of detection (POD = 0.82) compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) (POD = 0.808) for all cloud cases. In particular, the agreement between the CALIPSO cloud product and new GOCI cloud mask was over 94% when detecting thin cloud (e.g., altostratus and cirrus) from January 2014 to June 2015. This result is relatively high in comparison with the result from the MODIS Collection 6 cloud mask product (MYD35).

Improvements in Near-Terminator and Nocturnal Cloud Masks using Satellite Imager Data over the Atmospheric Radiation Measurement Sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trepte, Q.Z.; Minnis, P.; Heck, P.W.

2005-03-18

Cloud detection using satellite measurements presents a big challenge near the terminator where the visible (VIS; 0.65 {micro}m) channel becomes less reliable and the reflected solar component of the solar infrared 3.9-{micro}m channel reaches very low signal-to-noise ratio levels. As a result, clouds are underestimated near the terminator and at night over land and ocean in previous Atmospheric Radiation Measurement (ARM) Program cloud retrievals using Geostationary Operational Environmental Satellite (GOES) imager data. Cloud detection near the terminator has always been a challenge. For example, comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer [AVHRR]) cloud coverage and Geosciencemore » Laser Altimeter System (GLAS) measurements north of 60{sup o}N indicate significant amounts of missing clouds from AVHRR because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products and GLAS at the same regions also shows the same difficulty in the MODIS cloud retrieval (Pavolonis and Heidinger 2005). Consistent detection of clouds at all times of day is needed to provide reliable cloud and radiation products for ARM and other research efforts involving the modeling of clouds and their interaction with the radiation budget. To minimize inconsistencies between daytime and nighttime retrievals, this paper develops an improved twilight and nighttime cloud mask using GOES-9, 10, and 12 imager data over the ARM sites and the continental United States (CONUS).« less

Improvements in Near-Terminator and Nocturnal Cloud Masks using Satellite Image Data over the Atmospheric Radiation Measurement Sites

NASA Technical Reports Server (NTRS)

Trepte, Q. Z.; Minnis, P.; Heck, R. W.; Palikonda, R.

2005-01-01

Cloud detection using satellite measurements presents a big challenge near the terminator where the visible (VIS; 0.65 (micro)m) channel becomes less reliable and the reflected solar component of the solar infrared 3.9-(micro)m channel reaches very low signal-to-noise ratio levels. As a result, clouds are underestimated near the terminator and at night over land and ocean in previous Atmospheric Radiation Measurement (ARM) Program cloud retrievals using Geostationary Operational Environmental Satellite (GOES) imager data. Cloud detection near the terminator has always been a challenge. For example, comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer (AVHRR)) cloud coverage and Geoscience Laser Altimeter System (GLAS) measurements north of 60 degrees N indicate significant amounts of missing clouds from AVHRR because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products and GLAS at the same regions also shows the same difficulty in the MODIS cloud retrieval (Pavolonis and Heidinger 2005). Consistent detection of clouds at all times of day is needed to provide reliable cloud and radiation products for ARM and other research efforts involving the modeling of clouds and their interaction with the radiation budget. To minimize inconsistencies between daytime and nighttime retrievals, this paper develops an improved twilight and nighttime cloud mask using GOES-9, 10, and 12 imager data over the ARM sites and the continental United States (CONUS).

Arctic Clouds Infrared Imaging Field Campaign Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shaw, J. A.

2016-03-01

The Infrared Cloud Imager (ICI), a passive thermal imaging system, was deployed at the North Slope of Alaska site in Barrow, Alaska, from July 2012 to July 2014 for measuring spatial-temporal cloud statistics. Thermal imaging of the sky from the ground provides high radiometric contrast during night and polar winter when visible sensors and downward-viewing thermal sensors experience low contrast. In addition to demonstrating successful operation in the Arctic for an extended period and providing data for Arctic cloud studies, a primary objective of this deployment was to validate novel instrument calibration algorithms that will allow more compact ICI instrumentsmore » to be deployed without the added expense, weight, size, and operational difficulty of a large-aperture onboard blackbody calibration source. This objective was successfully completed with a comparison of the two-year data set calibrated with and without the onboard blackbody. The two different calibration methods produced daily-average cloud amount data sets with correlation coefficient = 0.99, mean difference = 0.0029 (i.e., 0.29% cloudiness), and a difference standard deviation = 0.054. Finally, the ICI instrument generally detected more thin clouds than reported by other ARM cloud products available as of late 2015.« less

Landsat 7 Reveals Large-scale Fractal Motion of Clouds

NASA Technical Reports Server (NTRS)

2002-01-01

This Landsat 7 image of clouds off the Chilean coast near the Juan Fernandez Islands (also known as the Robinson Crusoe Islands) on September 15, 1999, shows a unique pattern called a 'von Karman vortex street.' This pattern has long been studied in the laboratory, where the vortices are created by oil flowing past a cylindrical obstacle, making a string of vortices only several tens of centimeters long. Study of this classic 'flow past a circular cylinder' has been very important in the understanding of laminar and turbulent fluid flow that controls a wide variety of phenomena, from the lift under an aircraft wing to Earth's weather. Here, the cylinder is replaced by Alejandro Selkirk Island (named after the true 'Robinson Crusoe,' who was stranded here for many months in the early 1700s). The island is about 1.5 km in diameter, and rises 1.6 km into a layer of marine stratocumulus clouds. This type of cloud is important for its strong cooling of the Earth's surface, partially counteracting the Greenhouse warming. An extended, steady equatorward wind creates vortices with clockwise flow off the eastern edge and counterclockwise flow off the western edge of the island. The vortices grow as they advect hundreds of kilometers downwind, making a street 10,000 times longer than those made in the laboratory. Observing the same phenomenon extended over such a wide range of sizes dramatizes the 'fractal' nature of atmospheric convection and clouds. Fractals are characteristic of fluid flow and other dynamic systems that exhibit 'chaotic' motions. Both clockwise and counter-clockwise vortices are generated by flow around the island. As the flow separates from the island's leeward (away from the source of the wind) side, the vortices 'swallow' some of the clear air over the island. (Much of the island air is cloudless due to a local 'land breeze' circulation set up by the larger heat capacity of the waters surrounding the island.) The 'swallowed' gulps of clear island air get carried along within the vortices, but these are soon mixed into the surrounding clouds. Landsat is unique in its ability to image both the small-scale eddies that mix clear and cloudy air, down to the 30 meter pixel size of Landsat, but also having a wide enough field-of-view, 180 km, to reveal the connection of the turbulence to large-scale flows such as the subtropical oceanic gyres. Landsat 7, with its new onboard digital recorder, has extended this capability away from the few Landsat ground stations to remote areas such as Alejandro Island, and thus is gradually providing a global dynamic picture of evolving human-scale phenomena. (For more details on von Karman vortices, refer to http://climate.gsfc.nasa.gov/cahalan) Image and caption courtesy Bob Cahalan, NASA GSFC

Using Roving Cloud Observations from the S'COOL Project to Engage Citizen Scientists

NASA Astrophysics Data System (ADS)

Lewis, P. M.; Oostra, D.; Moore, S. W.; Rogerson, T. M.; Crecelius, S. A.; Chambers, L. H.

2011-12-01

Students' Clouds Observations On-Line (S'COOL) is a hands-on project, which supports NASA research on the Earth's climate. Through their observations, participants are engaged in identifying cloud-types and levels and sending that information to NASA. The two main groups of S'COOL observers are permanent locations such as regularly participating classrooms, and non-permanent locations or Rovers. These non-permanent locations can be a field trip, vacation, or just an occasional observation from a backyard. S'COOL welcomes participation from any interested observers, especially from places where official weather observations are few and far between. This program is offered to citizen scientists all over the world. They are participating in climate research by reporting cloud types and levels within +/- 15 minutes of a satellite overpass and sending that information back to NASA. When a participant's cloud observation coincides with a satellite overpass, the project sends them an email with a MODIS image of the overpass location, and a comparison of the satellite's cloud data results next to their ground-based report. This allows for the students and citizen scientists to participate in ground-truthing the CERES satellite data, to determine the level of agreement/disagreement. A new tool slated for future use in cloud identification, developed by the S'COOL team, is a mobile application. The application is entitled "Cloud Identification for Students" or "CITRUS". The mobile application utilizes a cloud dichotomous key with images to help with cloud identification. Also included in the application is a link to the project's cloud-reporting page to help with data submission in the field. One of the project's recent and most unique roving observers is a solo ocean rower who has traversed many of the world's ocean basins alone in a rowboat. While rowing across the oceans, she has recently been making cloud observations, which she sends back to us for analysis. In doing so, she is contributing difficult-to-collect ground-based data from points over the ocean, where there are typically no human inhabitants. As a result of the cloud reporting, we are able to better validate satellite data that give us a more complete picture of clouds in the atmosphere and their interactions with other parts of the integrated global Earth system. After making the cloud observations, students and citizen scientists are able to analyze the report they get back from NASA, improving their observation/data collection skills while keeping track of cloud patterns as they participate. Through the use of mobile technology, it will be possible to observe and immediately report the observation, allowing for a faster turn around on satellite reports and ground-truth data analysis. This paper will provide an analysis of the non-permanent observations made by the roving observers. These observations will give us an insight to their usefulness, as well as future steps for the program.

Correlation between atmospheric electric fields and cloud cover using a field mill and cloud observation data

NASA Astrophysics Data System (ADS)

Nakamori, Kota; Suzuki, Yasuki; Ohya, Hiroyo; Takano, Toshiaki; Kawamura, Yohei; Nakata, Hiroyuki; Yamashita, Kozo

2017-04-01

It is known that lightning and precipitations of rain droplets generated from thunderclouds are a generator of global atmospheric electric circuit. In the fair weather, the atmospheric electric fields (AEF) are downward (positive), while they are upward (negative) during lightning and precipitations. However, the correlations between the AEF, and the cloud parameters such as cloud cover, weather phenomenon, have been not revealed quantitatively yet. In this study, we investigate the correlations between the AEF and the cloud parameters, weather phenomenon using a field mill, the 95 GHz-FALCON (FMCW Radar for Cloud Observations)-I and all-sky camera observations. In this study, we installed a Boltek field mill on the roof of our building in Chiba University, Japan, (Geographic coordinate: 35.63 degree N, 140.10 degree E, the sea level: 55 m) on the first June, 2016. The sampling time of the AEF is 0.5 s. On the other hand, the FALCON-I has observed the cloud parameters far from about 76 m of the field mill throughout 24 hours every day. The vertical cloud profiles and the Doppler velocity of cloud particles can be derived by the FALCON-I with high distance resolutions (48.8 m) (Takano et al., 2010). In addition, the images of the clouds and precipitations are recorded with 30-s sampling by an all-sky camera using a CCD camera on the same roof during 05:00-22:00 LT every day. The distance between the field mill and the all-sky camera is 3.75 m. During 08:30 UT - 10:30 UT, on 4 July, 2016, we found the variation of the AEF due to the approach of thundercloud. The variation consisted of two patterns. One was slow variation due to the movement of thunderclouds, and the other was rapid variation associated with lightning discharges. As for the movement of thunderclouds, the AEF increased when the anvil was located over the field mill, which was opposite direction of the previous studies. This change might be due to the positive charges in the upper anvil more than 14 km altitude. As for the rapid variations of the AEF, 12 peaks of the AEF coincided with the occurrence of the lightning within 37 km. Moreover, we developed the automatic procedure to estimate the cloud cover from cloud optical images using the RGB color values. We estimated the correlation between the cloud cover and the AEF during June - November, 2016. The AEF decreased with increasing the cloud cover. This trend may be caused by the dielectric polarization due to the insert of the dielectric clouds into the global condenser. The standard deviation of AEF was small when the cloud cover increased. In this session, we will show the variations in the AEF during usual precipitations and snowing.

Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

NASA Technical Reports Server (NTRS)

Logan, T. L.; Huning, J. R.; Glackin, D. L.

1983-01-01

The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs.

Morning Clouds Atop Martian Mountain

NASA Image and Video Library

2015-06-19

Seen shortly after local Martian sunrise, clouds gather in the summit pit, or caldera, of Pavonis Mons, a giant volcano on Mars, in this image from the Thermal Emission Imaging System (THEMIS) on NASA's Mars Odyssey orbiter. The clouds are mostly made of ice crystals. They appear blue in the image because the cloud particles scatter blue light more strongly than other colors. Pavonis Mons stands about nine miles (14 kilometers) high, and the caldera spans about 29 miles (47 kilometers) wide. This image was made by THEMIS through three of its visual-light filters plus a near-infrared filter, and it is approximately true in color. THEMIS and other instruments on Mars Odyssey have been studying Mars from orbit since 2001. http://photojournal.jpl.nasa.gov/catalog/PIA19675

An approach of point cloud denoising based on improved bilateral filtering

NASA Astrophysics Data System (ADS)

Zheng, Zeling; Jia, Songmin; Zhang, Guoliang; Li, Xiuzhi; Zhang, Xiangyin

2018-04-01

An omnidirectional mobile platform is designed for building point cloud based on an improved filtering algorithm which is employed to handle the depth image. First, the mobile platform can move flexibly and the control interface is convenient to control. Then, because the traditional bilateral filtering algorithm is time-consuming and inefficient, a novel method is proposed which called local bilateral filtering (LBF). LBF is applied to process depth image obtained by the Kinect sensor. The results show that the effect of removing noise is improved comparing with the bilateral filtering. In the condition of off-line, the color images and processed images are used to build point clouds. Finally, experimental results demonstrate that our method improves the speed of processing time of depth image and the effect of point cloud which has been built.

Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

NASA Astrophysics Data System (ADS)

Su, X.

2017-12-01

A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

The benefit of limb cloud imaging for tropospheric infrared limb sounding

NASA Astrophysics Data System (ADS)

Adams, S.; Spang, R.; Preusse, P.; Heinemann, G.

2009-03-01

Advances in detector technology enable a new generation of infrared limb sounders to measure 2-D images of the atmosphere. A proposed limb cloud imager (LCI) mode will measure clouds with very high spatial resolution. For the inference of temperature and trace gas distributions, detector pixels of the LCI have to be combined into super-pixels which provide the required signal-to-noise ratio and information content for the retrievals. This study examines the extent to which tropospheric coverage can be improved in comparison to limb sounding using a fixed field of view with the size of the super-pixels, as in conventional limb sounders. The study is based on cloud topographies derived from (a) IR brightness temperatures (BT) of geostationary weather satellites in conjunction with ECMWF temperature profiles and (b) ice and liquid water content data of the Consortium for Small-scale Modeling-Europe (COSMO-EU) of the German Weather Service. Limb cloud images are simulated by matching the cloud topography with the limb sounding line of sight (LOS). The analysis of the BT data shows that the reduction of the spatial sampling along the track has hardly any effect on the gain in information. The comparison between BT and COSMO-EU data identifies the strength of both data sets, which are the representation of the horizontal cloud extent for the BT data and the reproduction of the cloud amount for the COSMO-EU data. The results of the analysis of both data sets show the great advantage of the cloud imager. However, because both cloud data sets do not present the complete fine structure of the real cloud fields in the atmosphere it is assumed that the results tend to underestimate the increase in information. In conclusion, real measurements by such an instrument may result in an even higher benefit for tropospheric limb retrievals.

The benefit of limb cloud imaging for infrared limb sounding of tropospheric trace gases

NASA Astrophysics Data System (ADS)

Adams, S.; Spang, R.; Preusse, P.; Heinemann, G.

2009-06-01

Advances in detector technology enable a new generation of infrared limb sounders to measure 2-D images of the atmosphere. A proposed limb cloud imager (LCI) mode will detect clouds with a spatial resolution unprecedented for limb sounding. For the inference of temperature and trace gas distributions, detector pixels of the LCI have to be combined into super-pixels which provide the required signal-to-noise and information content for the retrievals. This study examines the extent to which tropospheric coverage can be improved in comparison to limb sounding using a fixed field of view with the size of the super-pixels, as in conventional limb sounders. The study is based on cloud topographies derived from (a) IR brightness temperatures (BT) of geostationary weather satellites in conjunction with ECMWF temperature profiles and (b) ice and liquid water content data of the Consortium for Small-scale Modeling-Europe (COSMO-EU) of the German Weather Service. Limb cloud images are simulated by matching the cloud topography with the limb sounding line of sight (LOS). The analysis of the BT data shows that the reduction of the spatial sampling along the track has hardly any effect on the gain in information. The comparison between BT and COSMO-EU data identifies the strength of both data sets, which are the representation of the horizontal cloud extent for the BT data and the reproduction of the cloud amount for the COSMO-EU data. The results of the analysis of both data sets show the great advantage of the cloud imager. However, because both cloud data sets do not present the complete fine structure of the real cloud fields in the atmosphere it is assumed that the results tend to underestimate the increase in information. In conclusion, real measurements by such an instrument may result in an even higher benefit for tropospheric limb retrievals.

Cloud masking and removal in remote sensing image time series

NASA Astrophysics Data System (ADS)

Gómez-Chova, Luis; Amorós-López, Julia; Mateo-García, Gonzalo; Muñoz-Marí, Jordi; Camps-Valls, Gustau

2017-01-01

Automatic cloud masking of Earth observation images is one of the first required steps in optical remote sensing data processing since the operational use and product generation from satellite image time series might be hampered by undetected clouds. The high temporal revisit of current and forthcoming missions and the scarcity of labeled data force us to cast cloud screening as an unsupervised change detection problem in the temporal domain. We introduce a cloud screening method based on detecting abrupt changes along the time dimension. The main assumption is that image time series follow smooth variations over land (background) and abrupt changes will be mainly due to the presence of clouds. The method estimates the background surface changes using the information in the time series. In particular, we propose linear and nonlinear least squares regression algorithms that minimize both the prediction and the estimation error simultaneously. Then, significant differences in the image of interest with respect to the estimated background are identified as clouds. The use of kernel methods allows the generalization of the algorithm to account for higher-order (nonlinear) feature relations. After the proposed cloud masking and cloud removal, cloud-free time series at high spatial resolution can be used to obtain a better monitoring of land cover dynamics and to generate more elaborated products. The method is tested in a dataset with 5-day revisit time series from SPOT-4 at high resolution and with Landsat-8 time series. Experimental results show that the proposed method yields more accurate cloud masks when confronted with state-of-the-art approaches typically used in operational settings. In addition, the algorithm has been implemented in the Google Earth Engine platform, which allows us to access the full Landsat-8 catalog and work in a parallel distributed platform to extend its applicability to a global planetary scale.

Progress towards NASA MODIS and Suomi NPP Cloud Property Data Record Continuity

NASA Astrophysics Data System (ADS)

Platnick, S.; Meyer, K.; Holz, R.; Ackerman, S. A.; Heidinger, A.; Wind, G.; Platnick, S. E.; Wang, C.; Marchant, B.; Frey, R.

2017-12-01

The Suomi NPP VIIRS imager provides an opportunity to extend the 17+ year EOS MODIS climate data record into the next generation operational era. Similar to MODIS, VIIRS provides visible through IR observations at moderate spatial resolution with a 1330 LT equatorial crossing consistent with the MODIS on the Aqua platform. However, unlike MODIS, VIIRS lacks key water vapor and CO2 absorbing channels used for high cloud detection and cloud-top property retrievals. In addition, there is a significant mismatch in the spectral location of the 2.2 μm shortwave-infrared channels used for cloud optical/microphysical retrievals and cloud thermodynamic phase. Given these instrument differences between MODIS EOS and VIIRS S-NPP/JPSS, a merged MODIS-VIIRS cloud record to serve the science community in the coming decades requires different algorithm approaches than those used for MODIS alone. This new approach includes two parallel efforts: (1) Imager-only algorithms with only spectral channels common to VIIRS and MODIS (i.e., eliminate use of MODIS CO2 and NIR/IR water vapor channels). Since the algorithms are run with similar spectral observations, they provide a basis for establishing a continuous cloud data record across the two imagers. (2) Merged imager and sounder measurements (i.e.., MODIS-AIRS, VIIRS-CrIS) in lieu of higher-spatial resolution MODIS absorption channels absent on VIIRS. The MODIS-VIIRS continuity algorithm for cloud optical property retrievals leverages heritage algorithms that produce the existing MODIS cloud mask (MOD35), optical and microphysical properties product (MOD06), and the NOAA AWG Cloud Height Algorithm (ACHA). We discuss our progress towards merging the MODIS observational record with VIIRS in order to generate cloud optical property climate data record continuity across the observing systems. In addition, we summarize efforts to reconcile apparent radiometric biases between analogous imager channels, a critical consideration for obtaining inter-sensor climate data record continuity.

Ammonia Clouds on Jupiter

NASA Technical Reports Server (NTRS)

2007-01-01

[figure removed for brevity, see original site] Click on the image for movie of Ammonia Ice Clouds on Jupiter

In this movie, put together from false-color images taken by the New Horizons Ralph instrument as the spacecraft flew past Jupiter in early 2007, show ammonia clouds (appearing as bright blue areas) as they form and disperse over five successive Jupiter 'days.' Scientists noted how the larger cloud travels along with a small, local deep hole.

Benefits of cloud computing for PACS and archiving.

PubMed

Koch, Patrick

2012-01-01

The goal of cloud-based services is to provide easy, scalable access to computing resources and IT services. The healthcare industry requires a private cloud that adheres to government mandates designed to ensure privacy and security of patient data while enabling access by authorized users. Cloud-based computing in the imaging market has evolved from a service that provided cost effective disaster recovery for archived data to fully featured PACS and vendor neutral archiving services that can address the needs of healthcare providers of all sizes. Healthcare providers worldwide are now using the cloud to distribute images to remote radiologists while supporting advanced reading tools, deliver radiology reports and imaging studies to referring physicians, and provide redundant data storage. Vendor managed cloud services eliminate large capital investments in equipment and maintenance, as well as staffing for the data center--creating a reduction in total cost of ownership for the healthcare provider.

Photographer : JPL Range : 3.4 million km This pair of images shows two of the long-lived white oval

NASA Technical Reports Server (NTRS)

1979-01-01

Photographer : JPL Range : 3.4 million km This pair of images shows two of the long-lived white oval clouds which have resided in the Jovian southern hemisphere for nearly 40 years. The upper picture shows the cloud that is at a longitude west of the Great Red Spot, and the lower frame, the cloud at a longitude east of this feature. The third oval is currently just south of the Great Red Spot. The clouds show very similar internal structures. To the east of each of them, recirculation currents are clearly seen. In the lower frame, a similar structure is seen to the west of the cloud. Although a recirculation current is associated with the upper western region of the cloud, it is further away from this feature and not seen in the image. This photo was taken by Voyager 2.

Multi-band Emission Light Curves of Jupiter: Insights on Brown Dwarfs and Directly Imaged Exoplanets

NASA Astrophysics Data System (ADS)

Zhang, Xi; Ge, Huazhi; Orton, Glenn S.; Fletcher, Leigh N.; Sinclair, James; Fernandes, Joshua; Momary, Thomas W.; Kasaba, Yasumasa; Sato, Takao M.; Fujiyoshi, Takuya

2016-10-01

Many brown dwarfs exhibit significant infrared flux variability (e.g., Artigau et al. 2009, ApJ, 701, 1534; Radigan et al. 2012, ApJ, 750, 105), ranging from several to twenty percent of the brightness. Current hypotheses include temperature variations, cloud holes and patchiness, and cloud height and thickness variations (e.g., Apai et al. 2013, ApJ, 768, 121; Robinson and Marley 2014, ApJ, 785, 158; Zhang and Showman 2014, ApJ, 788, L6). Some brown dwarfs show phase shifts in the light curves among different wavelengths (e.g., Buenzli et al. 2012, ApJ, 760, L31; Yang et al. 2016, arXiv:1605.02708), indicating vertical variations of the cloud distribution. The current observational technique can barely detect the brightness changes on the surfaces of nearby brown dwarfs (Crossfield et al. 2014, Nature, 505, 654) let alone resolve detailed weather patterns that cause the flux variability. The infrared emission maps of Jupiter might shed light on this problem. Using COMICS at Subaru Telescope, VISIR at Very Large Telescope (VLT) and NASA's Infrared Telescope Facility (IRTF), we obtained infrared images of Jupiter over several nights at multiple wavelengths that are sensitive to several pressure levels from the stratosphere to the deep troposphere below the ammonia clouds. The rotational maps and emission light curves are constructed. The individual pixel brightness varies up to a hundred percent level and the variation of the full-disk brightness is around several percent. Both the shape and amplitude of the light curves are significantly distinct at different wavelengths. Variation of light curves at different epochs and phase shift among different wavelengths are observed. We will present principle component analysis to identify dominant emission features such as stable vortices, cloud holes and eddies in the belts and zones and strong emissions in the aurora region. A radiative transfer model is used to simulate those features to get a more quantitative understanding. This work provides rich insights on the relationship between observed light curves and weather on brown dwarfs and perhaps on directly imaged exoplanets in the future.

The application of time series models to cloud field morphology analysis

NASA Technical Reports Server (NTRS)

Chin, Roland T.; Jau, Jack Y. C.; Weinman, James A.

1987-01-01

A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

Dome flat-field system for 1.3-m Araki Telescope

NASA Astrophysics Data System (ADS)

Yoshikawa, Tomohiro; Ikeda, Yuji; Fujishiro, Naofumi; Ichizawa, Shunsuke; Arai, Akira; Isogai, Mizuki; Yonehara, Atsunori; Kawakita, Hideyo

2012-09-01

We report the system/optics design and performance of the dome flat-field system for the Araki Telescope, a 1.3- m optical/near-infrared telescope at Koyama Astronomical Observatory in Japan. A variety of instruments are attached to the telescope. The optical imager, which is intended to search for exoplanets, requires an illumination flatness within 1% on the focal plane over the 17-arcmin FOV. Illumination flatness at both the pupil plane and the focal plane of the telescope is essential for calibration of the transmittance of the optical system. We devised an optical design for the flat-field system that satisfies illumination flatness at both the focal and pupil planes using the non-sequential ray tracing software LightTools. We considered far-field illumination pattern of the lamps, scattering surface reflectance distribution of the screen, telescope structure, primary/secondary mirrors, and mirror baffles. We achieved a flat illumination distribution of 0.9% at the focal plane. The systems performance was tested by comparison with a cloud-flat frame, which was derived by imaging cloud cover illuminated by city lights. The calibration data for the dome flat-field system agree well with the cloud-flat frame within 1% for the g' and i' bands of the imager, but the r0 band data does not meet the requirement (less than or equal to 2). Moreover, various instruments require a focal plane illuminance ranging over three orders of magnitude. We used six high-power (60W) halogen lamps; the output power is remotely controlled by a thyristor-driven dimmer and a bypass circuit to an autotransformer.

Airborne Sea of Dust over China

NASA Technical Reports Server (NTRS)

2002-01-01

TDust covered northern China in the last week of March during some of the worst dust storms to hit the region in a decade. The dust obscuring China's Inner Mongolian and Shanxi Provinces on March 24, 2002, is compared with a relatively clear day (October 31, 2001) in these images from the Multi-angle Imaging SpectroRadiometer's vertical-viewing (nadir) camera aboard NASA's Terra satellite. Each image represents an area of about 380 by 630 kilometers (236 by 391 miles). In the image from late March, shown on the right, wave patterns in the yellowish cloud liken the storm to an airborne ocean of dust. The veil of particulates obscures features on the surface north of the Yellow River (visible in the lower left). The area shown lies near the edge of the Gobi desert, a few hundred kilometers, or miles, west of Beijing. Dust originates from the desert and travels east across northern China toward the Pacific Ocean. For especially severe storms, fine particles can travel as far as North America. The Multi-angle Imaging SpectroRadiometer, built and managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., is one of five Earth-observing instruments aboard the Terra satellite, launched in December 1999. The instrument acquires images of Earth at nine angles simultaneously, using nine separate cameras pointed forward, downward and backward along its flight path. The change in reflection at different view angles affords the means to distinguish different types of atmospheric particles, cloud forms and land surface covers. Image courtesy NASA/GSFC/LaRC/JPL, MISR Team

MISR Global Images See the Light of Day

NASA Technical Reports Server (NTRS)

2002-01-01

As of July 31, 2002, global multi-angle, multi-spectral radiance products are available from the MISR instrument aboard the Terra satellite. Measuring the radiative properties of different types of surfaces, clouds and atmospheric particulates is an important step toward understanding the Earth's climate system. These images are among the first planet-wide summary views to be publicly released from the Multi-angle Imaging SpectroRadiometer experiment. Data for these images were collected during the month of March 2002, and each pixel represents monthly-averaged daylight radiances from an area measuring 1/2 degree in latitude by 1/2 degree in longitude.

The top panel is from MISR's nadir (vertical-viewing) camera and combines data from the red, green and blue spectral bands to create a natural color image. The central view combines near-infrared, red, and green spectral data to create a false-color rendition that enhances highly vegetated terrain. It takes 9 days for MISR to view the entire globe, and only areas within 8 degrees of latitude of the north and south poles are not observed due to the Terra orbit inclination. Because a single pole-to-pole swath of MISR data is just 400 kilometers wide, multiple swaths must be mosaiced to create these global views. Discontinuities appear in some cloud patterns as a consequence of changes in cloud cover from one day to another.

The lower panel is a composite in which red, green, and blue radiances from MISR's 70-degree forward-viewing camera are displayed in the northern hemisphere, and radiances from the 70-degree backward-viewing camera are displayed in the southern hemisphere. At the March equinox (spring in the northern hemisphere, autumn in the southern hemisphere), the Sun is near the equator. Therefore, both oblique angles are observing the Earth in 'forward scattering', particularly at high latitudes. Forward scattering occurs when you (or MISR) observe an object with the Sun at a point in the sky that is in front of you. Relative to the nadir view, this geometry accentuates the appearance of polar clouds, and can even reveal clouds that are invisible in the nadir direction. In relatively clear ocean areas, the oblique-angle composite is generally brighter than its nadir counterpart due to enhanced reflection of light by atmospheric particulates.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Absorption of solar energy heats up our planet's surface and the atmosphere and makes life for us po

NASA Technical Reports Server (NTRS)

2002-01-01

Credit: Image courtesy Barbara Summey, NASA Goddard Visualization Analysis Lab, based upon data processed by Takmeng Wong, CERES Science Team, NASA Langley Research Center Satellite: Terra Sensor: CERES Image Date: 09-30-2001 VE Record ID: 11546 Description: Absorption of solar energy heats up our planet's surface and the atmosphere and makes life for us possible. But the energy cannot stay bound up in the Earth's environment forever. If it did then the Earth would be as hot as the Sun. Instead, as the surface and the atmosphere warm, they emit thermal longwave radiation, some of which escapes into space and allows the Earth to cool. This false-color image of the Earth was produced on September 30, 2001, by the Clouds and the Earth's Radiant Energy System (CERES) instrument flying aboard NASA's Terra spacecraft. The image shows where more or less heat, in the form of longwave radiation, is emanating from the top of Earth's atmosphere. As one can see in the image, the thermal radiation leaving the oceans is fairly uniform. The blue swaths across the central Pacific represent thick clouds, the tops of which are so high they are among the coldest places on Earth. In the American Southwest, which can be seen in the upper righthand corner of the globe, there is often little cloud cover to block outgoing radiation and relatively little water to absorb solar energy. Consequently, the amount of outgoing radiation in the American Southwest exceeds that of the oceans. Also, that region was experiencing an extreme heatwave when these data were acquired. Recently, NASA researchers discovered that incoming solar radiation and outgoing thermal radiation increased in the tropics from the 1980s to the 1990s. (Click to read the press release .) They believe that the reason for the unexpected increase has to do with an apparent change in circulation patterns around the globe, which effectively reduced the amount of water vapor and cloud cover in the upper reaches of the atmosphere. Without the clouds, more sunlight was allowed to enter the tropical zones and more thermal energy was allowed to leave. The findings may have big implications for climate change and future global warming. 'This suggests that the tropical heat engine increased its speed,' observes Dr. Bruce Wielicki, of NASA Langley Research Center. 'It's as if the heat engine in the tropics has become less efficient, using more fuel in the 1990s than in the 1980s.'

A computer vision approach for solar radiation nowcasting using MSG images

NASA Astrophysics Data System (ADS)

Álvarez, L.; Castaño Moraga, C. A.; Martín, J.

2010-09-01

Cloud structures and haze are the two main atmospheric phenomena that reduce the performance of solar power plants, since they absorb solar energy reaching terrestrial surface. Thus, accurate forecasting of solar radiation is a challenging research area that involves both a precise localization of cloud structures and haze, as well as the attenuation introduced by these artifacts. Our work presents a novel approach for nowcasting services based on image processing techniques applied to MSG satellite images provided by the EUMETSAT Rapid Scan Service (RSS) service. These data are an interesting source of information for our purposes since every 5 minutes we obtain actual information of the atmospheric state in nearly real time. However, a workaround must be given in order to forecast solar radiation. To that end, we synthetically forecast MSG images forecasts from past images applying computer vision techniques adapted to fluid flows in order to evolve atmospheric state. First, we classify cloud structures on two different layers, corresponding to top and bottom clouds, which includes haze. This two-level classification responds to the dominant climate conditions found in our region of interest, the Canary Islands archipelago, regulated by the Gulf Stream and Trade Winds. Vertical structure of Trade Winds consists of two layers, the bottom one, which is fresh and humid, and the top one, which is warm and dry. Between these two layers a thermal inversion appears that does not allow bottom clouds to go up and naturally divides clouds in these two layers. Top clouds can be directly obtained from satellite images by means of a segmentation algorithm on histogram heights. However, bottom clouds are usually overlapped by the former, so an inpainting algorithm is used to recover overlapped areas of bottom clouds. For each layer, cloud motion is estimated through a correlation based optic flow algorithm that provides a vector field that describes the displacement field in each layer between two consecutive images in a sequence. Since RSS service from EUMETSAT provides images every 5 minutes (Δt), the cloud motion vector field between images at time t0 and (t0 - Δt) is quite similar to that between (t0 - Δt) and (t0 - 2Δt). Under this assumption, we infer the motion vector field for the next image in order to build a synthetic version of the image at time (t0 + Δt). The computation of this future motion vector field takes into account terrain orography in order to produce more realistic forecasts. In this sense, we are currently working on the integration of information from NWP outputs in order to introduce other atmospheric phenomena. Applying this algorithm several times we are able to produce short-term forecasts up to 6 hours with encouraging performance. To validate our results, we use both, comparison of synthetically generated images with the corresponding images at a given time, and direct solar radiation measurement with the set of meteorological stations located at several points of the canarian archipelago.

Venus in Violet and Near Infrared Light

NASA Image and Video Library

1996-02-01

These images of the Venus clouds were taken by NASA Galileo Solid State Imaging System February 13,1990, at a range of about 1 million miles. The smallest detail visible is about 20 miles. They show the state of the clouds near the top of Venus cloud. http://photojournal.jpl.nasa.gov/catalog/PIA00071

Mars topographic clouds: MAVEN/IUVS observations and LMD MGCM predictions

NASA Astrophysics Data System (ADS)

Schneider, Nicholas M.; Connour, Kyle; Forget, Francois; Deighan, Justin; Jain, Sonal; Vals, Margaux; Wolff, Michael J.; Chaffin, Michael S.; Crismani, Matteo; Stewart, A. Ian F.; McClintock, William E.; Holsclaw, Greg; Lefevre, Franck; Montmessin, Franck; Stiepen, Arnaud; Stevens, Michael H.; Evans, J. Scott; Yelle, Roger; Lo, Daniel; Clarke, John T.; Jakosky, Bruce

2017-10-01

The Imaging Ultraviolet Spectrograph (IUVS) instrument on the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft takes mid-UV spectral images of the Martian atmosphere. From these apoapse disk images, information about clouds and aerosols can be retrieved and comprise the only MAVEN observations of topographic clouds and cloud morphologies. Measuring local time variability of large-scale recurring cloud features is made possible with MAVEN’s ~4.5-hour elliptical orbit, something not possible with sun-synchronous orbits. We have run the LMD MGCM (Mars global circulation model) at 1° x 1° resolution to simulate water ice cloud formation with inputs consistent with observing parameters and Mars seasons. Topographic clouds are observed to form daily during the late mornings of northern hemisphere spring and this phenomenon recurs until late summer (Ls = 160°), after which topographic clouds wane in thickness. By northern fall, most topographic clouds cease to form except over Arsia Mons and Pavonis Mons, where clouds can still be observed. Our data show moderate cloud formation over these regions as late as Ls = 220°, something difficult for the model to replicate. Previous studies have shown that models have trouble simulating equatorial cloud thickness in combination with a realistic amount of water vapor and not-too-thick polar water ice clouds, implying aspects of the water cycle are not fully understood. We present data/model comparisons as well as further refinements on parameter inputs based on IUVS observations.

Mars topographic clouds: MAVEN/IUVS observations and LMD MGCM predictions

NASA Astrophysics Data System (ADS)

Connour, K.; Schneider, N.; Forget, F.; Deighan, J.; Jain, S.; Pottier, A.; Wolff, M. J.; Chaffin, M.; Crismani, M. M. J.; Stewart, I. F.; McClintock, B.; Holsclaw, G.; Lefèvre, F.; Montmessin, F.; Stiepen, A.; Stevens, M. H.; Evans, J. S.; Yelle, R. V.; Lo, D.; Clarke, J. T.; Jakosky, B. M.

2017-12-01

The Imaging Ultraviolet Spectrograph (IUVS) instrument on the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft takes mid-UV spectral images of the Martian atmosphere. From these apoapse disk images, information about clouds and aerosols can be retrieved and comprise the only MAVEN observations of topographic clouds and cloud morphologies. Measuring local time variability of large-scale recurring cloud features is made possible with MAVEN's 4.5-hour elliptical orbit, something not possible with sun-synchronous orbits. We have run the LMD MGCM (Mars global circulation model) at 1° x 1° resolution to simulate water ice cloud formation with inputs consistent with observing parameters and Mars seasons. Topographic clouds are observed to form daily during the late mornings of northern hemisphere spring and this phenomenon recurs until late summer (Ls = 160°), after which topographic clouds wane in thickness. By northern fall, most topographic clouds cease to form except over Arsia Mons and Pavonis Mons, where clouds can still be observed. Our data show moderate cloud formation over these regions as late as Ls = 220°, something difficult for the model to replicate. Previous studies have shown that models have trouble simulating equatorial cloud thickness in combination with a realistic amount of water vapor and not-too-thick polar water ice clouds, implying aspects of the water cycle are not fully understood. We present data/model comparisons as well as further refinements on parameter inputs based on IUVS observations.

Stellar Snowflake Cluster

NASA Technical Reports Server (NTRS)

2005-01-01

[figure removed for brevity, see original site] Figure 1 Stellar Snowflake Cluster Combined Image [figure removed for brevity, see original site] Figure 2 Infrared Array CameraFigure 3 Multiband Imaging Photometer

Newborn stars, hidden behind thick dust, are revealed in this image of a section of the Christmas Tree cluster from NASA's Spitzer Space Telescope, created in joint effort between Spitzer's infrared array camera and multiband imaging photometer instruments.

The newly revealed infant stars appear as pink and red specks toward the center of the combined image (fig. 1). The stars appear to have formed in regularly spaced intervals along linear structures in a configuration that resembles the spokes of a wheel or the pattern of a snowflake. Hence, astronomers have nicknamed this the 'Snowflake' cluster.

Star-forming clouds like this one are dynamic and evolving structures. Since the stars trace the straight line pattern of spokes of a wheel, scientists believe that these are newborn stars, or 'protostars.' At a mere 100,000 years old, these infant structures have yet to 'crawl' away from their location of birth. Over time, the natural drifting motions of each star will break this order, and the snowflake design will be no more.

While most of the visible-light stars that give the Christmas Tree cluster its name and triangular shape do not shine brightly in Spitzer's infrared eyes, all of the stars forming from this dusty cloud are considered part of the cluster.

Like a dusty cosmic finger pointing up to the newborn clusters, Spitzer also illuminates the optically dark and dense Cone nebula, the tip of which can be seen towards the bottom left corner of each image.

This combined image shows the presence of organic molecules mixed with dust as wisps of green, which have been illuminated by nearby star formation. The larger yellowish dots neighboring the baby red stars in the Snowflake Cluster are massive stellar infants forming from the same cloud. The blue dots sprinkled across the image represent older Milky Way stars at various distances along this line of sight. This image is a five-channel, false-color composite, showing emission from wavelengths of 3.6 and 4.5 microns (blue), 5.8 microns (cyan), 8 microns (green), and 24 microns (red).

The top right (fig. 2) image from the infrared array camera show that the nebula is still actively forming stars. The wisps of red (represented as green in the combined image) are organic molecules mixed with dust, which has been illuminated by nearby star formation. The infrared array camera picture is a four-channel, false-color composite, showing emission from wavelengths of 3.6 microns (blue), 4.5 microns (green), 5.8 microns (orange) and 8.0 microns (red).

The bottom right image (fig. 3) from the multiband imaging photometer shows the colder dust of the nebula and unwraps the youngest stellar babies from their dusty covering. This is a false-color image showing emission at 24 microns (red).

Detection of long duration cloud contamination in hyper-temporal NDVI imagery

NASA Astrophysics Data System (ADS)

Ali, A.; de Bie, C. A. J. M.; Skidmore, A. K.; Scarrott, R. G.

2012-04-01

NDVI time series imagery are commonly used as a reliable source for land use and land cover mapping and monitoring. However long duration cloud can significantly influence its precision in areas where persistent clouds prevails. Therefore quantifying errors related to cloud contamination are essential for accurate land cover mapping and monitoring. This study aims to detect long duration cloud contamination in hyper-temporal NDVI imagery based land cover mapping and monitoring. MODIS-Terra NDVI imagery (250 m; 16-day; Feb'03-Dec'09) were used after necessary pre-processing using quality flags and upper envelope filter (ASAVOGOL). Subsequently stacked MODIS-Terra NDVI image (161 layers) was classified for 10 to 100 clusters using ISODATA. After classifications, 97 clusters image was selected as best classified with the help of divergence statistics. To detect long duration cloud contamination, mean NDVI class profiles of 97 clusters image was analyzed for temporal artifacts. Results showed that long duration clouds affect the normal temporal progression of NDVI and caused anomalies. Out of total 97 clusters, 32 clusters were found with cloud contamination. Cloud contamination was found more prominent in areas where high rainfall occurs. This study can help to stop error propagation in regional land cover mapping and monitoring, caused by long duration cloud contamination.

Clouds and the Earth's Radiant Energy System (CERES) Algorithm Theoretical Basis Document. Volume 3; Cloud Analyses and Determination of Improved Top of Atmosphere Fluxes (Subsystem 4)

NASA Technical Reports Server (NTRS)

1995-01-01

The theoretical bases for the Release 1 algorithms that will be used to process satellite data for investigation of the Clouds and Earth's Radiant Energy System (CERES) are described. The architecture for software implementation of the methodologies is outlined. Volume 3 details the advanced CERES methods for performing scene identification and inverting each CERES scanner radiance to a top-of-the-atmosphere (TOA) flux. CERES determines cloud fraction, height, phase, effective particle size, layering, and thickness from high-resolution, multispectral imager data. CERES derives cloud properties for each pixel of the Tropical Rainfall Measuring Mission (TRMM) visible and infrared scanner and the Earth Observing System (EOS) moderate-resolution imaging spectroradiometer. Cloud properties for each imager pixel are convolved with the CERES footprint point spread function to produce average cloud properties for each CERES scanner radiance. The mean cloud properties are used to determine an angular distribution model (ADM) to convert each CERES radiance to a TOA flux. The TOA fluxes are used in simple parameterization to derive surface radiative fluxes. This state-of-the-art cloud-radiation product will be used to substantially improve our understanding of the complex relationship between clouds and the radiation budget of the Earth-atmosphere system.

Region-Based Prediction for Image Compression in the Cloud.

PubMed

Begaint, Jean; Thoreau, Dominique; Guillotel, Philippe; Guillemot, Christine

2018-04-01

Thanks to the increasing number of images stored in the cloud, external image similarities can be leveraged to efficiently compress images by exploiting inter-images correlations. In this paper, we propose a novel image prediction scheme for cloud storage. Unlike current state-of-the-art methods, we use a semi-local approach to exploit inter-image correlation. The reference image is first segmented into multiple planar regions determined from matched local features and super-pixels. The geometric and photometric disparities between the matched regions of the reference image and the current image are then compensated. Finally, multiple references are generated from the estimated compensation models and organized in a pseudo-sequence to differentially encode the input image using classical video coding tools. Experimental results demonstrate that the proposed approach yields significant rate-distortion performance improvements compared with the current image inter-coding solutions such as high efficiency video coding.

New Observations and Studies of Saturn's Long-Lived North Polar SPOT

NASA Astrophysics Data System (ADS)

Sanchez-Lavega, Agustin; Rojas, Jose Félix; Acarreta, Juan Ramón; Lecacheux, Jean; Colas, François; Sada, Pedro V.

1997-08-01

We report on a new series of ground-based CCD observations at visual wavelengths, covering a period of 1255 days between May 1992 and November 1995, of the longest-lived asymmetric feature known in Saturn's atmosphere: the north polar spot (NPS). This completes our previous analysis of this feature during the period 1990-1991 (A. Sanchez-Lavega, J. Lecacheux, F. Colas, and P. Lagues, 1993,Science260,329-332). Longitude measurements of the NPS indicate an averaged longitudinal drift of -0.030 deg/day for the whole period 1990-1995 corresponding to a zonal velocity of 0.11 msec-1. These data, when combined with previous and new measurements of the NPS position on Voyager 1 and 2 images obtained in 1980 and 1981, indicate a long-term drift in longitude of the NPS with a constant angular acceleration of 1.1 × 10-5deg/(day)2. High-resolution Voyager 2 violet, blue, green, and orange images were used to measure the size and reflectivity of the NPS. Its structure is characterized by a bright elliptical core surrounded by a dark ring and a large uniform area. The contrast between all these features changes appreciably from violet to orange: the spot is dark in violet but bright in orange relative to its surroundings. The spot is embedded within a region seeded by a “field of bright clouds” with characteristic size 1000 km reminiscent of a cellular convection pattern. The NPS's east-west apparent size is shorter at violet-blue (about 7000 km as limited by a dark ring at these wavelengths) than at green-orange (about 11,000 km corresponding to the large uniform area). Green processed images show apparent spiral patterns within the NPS consistent with anticyclonic vorticity. The results of ground-based photometry of the north polar region (NPR) and the NPS in the red methane absorption bands and their adjacent continuum are consistent with a radiative transfer model of the cloud vertical structure consisting of a clear gas layer, a haze layer, and a semi-infinite cloud. In the context of this model the NPS cloud tops are slightly higher than neighboring clouds reaching a pressure level of 45 mbar. Calculations of the seasonal insolation at the north pole, together with a simple linear radiative response of the atmosphere to this heating at different altitudes, suggest temperature changes at the level of the NPS cloud tops which should influence the NPS dynamics. Because of the long lifetime of the NPS, and because its motions did not vary appreciably during the long observing period, we suggest that the main properties and dynamics of the NPS are insensitive to the external solar forcing.

Analysis of aerosol-cloud-precipitation interactions based on MODIS data

NASA Astrophysics Data System (ADS)

Cheng, Feng; Zhang, Jiahua; He, Junliang; Zha, Yong; Li, Qiannan; Li, Yunmei

2017-01-01

Aerosols exert an indirect impact on climate change via its impact on clouds by altering its radiative and optical properties which, in turn, changes the process of precipitation. Over recent years how to study the indirect climate effect of aerosols has become an important research topic. In this study we attempted to understand the complex mutual interactions among aerosols, clouds and precipitation through analysis of the spatial correlation between aerosol optical depth (AOD), cloud effective radius (CER) and precipitation during 2000-2012 in central-eastern China that has one of the highest concentrations of aerosols globally. With the assistance of moderate resolution imaging spectroradiometer (MODIS)-derived aerosol and cloud product data, this analysis focuses on regional differentiation and seasonal variation of the correlation in which in situ observed precipitation was incorporated. On the basis of the achieved results, we proposed four patterns depicting the mutual interactions between aerosols, clouds and precipitation. They characterize the indirect effects of aerosols on the regional scale. These effects can be summarized as complex seasonal variations and north-south regional differentiation over the study area. The relationship between AOD and CER is predominated mostly by the first indirect effect (the negative correlation between AOD and CER) in the north of the study area in the winter and spring seasons, and over the entire study area in the summer season. The relationship between CER and precipitation is dominated chiefly by the second indirect effect (the positive correlation between CER and precipitation) in the northern area in summer and over the entire study area in autumn. It must be noted that aerosols are not the factor affecting clouds and rainfall singularly. It is the joint effect of aerosols with other factors such as atmospheric dynamics that governs the variation in clouds and rainfall.

Fast Track to the Cloud: Design Patterns for 12-Factor Earth Sciences Applications

NASA Technical Reports Server (NTRS)

Pawloski, Andrew; McLaughlin, Brett; Lynnes, Christopher

2016-01-01

As expanding service offerings and decreasing prices make the cloud increasingly attractive to Earth Science applications, there are nontrivial practical considerations which can hinder its meaningful use. In this talk, we will discuss architectural recommendations and lessons learned while working on EOSDIS' cloud efforts, particularly the NASA-compliant General Application Platform (NGAP) and its associated applications. Prominent in our findings is the importance of 12-factor design patterns and the powerful "wins" they enable in the cloud. We will share our strategies for "fast-tracking" applications to the cloud --whether they be legacy, planned for the future, or somewhere in between.

Jovian Lightning and Moonlit Clouds

NASA Technical Reports Server (NTRS)

1997-01-01

Jovian lightning and moonlit clouds. These two images, taken 75 minutes apart, show lightning storms on the night side of Jupiter along with clouds dimly lit by moonlight from Io, Jupiter's closest moon. The images were taken in visible light and are displayed in shades of red. The images used an exposure time of about one minute, and were taken when the spacecraft was on the opposite side of Jupiter from the Earth and Sun. Bright storms are present at two latitudes in the left image, and at three latitudes in the right image. Each storm was made visible by multiple lightning strikes during the exposure. Other Galileo images were deliberately scanned from east to west in order to separate individual flashes. The images show that Jovian and terrestrial lightning storms have similar flash rates, but that Jovian lightning strikes are a few orders of magnitude brighter in visible light.

The moonlight from Io allows the lightning storms to be correlated with visible cloud features. The latitude bands where the storms are seen seem to coincide with the 'disturbed regions' in daylight images, where short-lived chaotic motions push clouds to high altitudes, much like thunderstorms on Earth. The storms in these images are roughly one to two thousand kilometers across, while individual flashes appear hundreds of kilometer across. The lightning probably originates from the deep water cloud layer and illuminates a large region of the visible ammonia cloud layer from 100 kilometers below it.

There are several small light and dark patches that are artifacts of data compression. North is at the top of the picture. The images span approximately 50 degrees in latitude and longitude. The lower edges of the images are aligned with the equator. The images were taken on October 5th and 6th, 1997 at a range of 6.6 million kilometers by the Solid State Imaging (SSI) system on NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the Galileo mission for NASA's Office of Space Science, Washington, DC. JPL is an operating division of California Institute of Technology (Caltech).

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov.

The identification of cloud types in LANDSAT MSS images. [Great Britain

NASA Technical Reports Server (NTRS)

Barrett, E. C. (Principal Investigator); Grant, C. K.

1976-01-01

The author has identified the following significant results. Five general families of clouds were identified: cumulonimbiform, cumuliform, stratiform, stratocumuliform, and cirriform. Four members of this five-fold primary division of clouds were further divided into a number of subgroups. The MSS observed and recorded earth radiation in four different wavebands. Two of these bands (4 and 5) image in the visible portion of the electromagnetic spectrum, while the others (6 and 7) image the short wave portion, or just into the infrared. The main differences between the appearances of clouds in the four wavebands are related to the background brightness of land and sea surfaces.

ScipionCloud: An integrative and interactive gateway for large scale cryo electron microscopy image processing on commercial and academic clouds.

PubMed

Cuenca-Alba, Jesús; Del Cano, Laura; Gómez Blanco, Josué; de la Rosa Trevín, José Miguel; Conesa Mingo, Pablo; Marabini, Roberto; S Sorzano, Carlos Oscar; Carazo, Jose María

2017-10-01

New instrumentation for cryo electron microscopy (cryoEM) has significantly increased data collection rate as well as data quality, creating bottlenecks at the image processing level. Current image processing model of moving the acquired images from the data source (electron microscope) to desktops or local clusters for processing is encountering many practical limitations. However, computing may also take place in distributed and decentralized environments. In this way, cloud is a new form of accessing computing and storage resources on demand. Here, we evaluate on how this new computational paradigm can be effectively used by extending our current integrative framework for image processing, creating ScipionCloud. This new development has resulted in a full installation of Scipion both in public and private clouds, accessible as public "images", with all the required preinstalled cryoEM software, just requiring a Web browser to access all Graphical User Interfaces. We have profiled the performance of different configurations on Amazon Web Services and the European Federated Cloud, always on architectures incorporating GPU's, and compared them with a local facility. We have also analyzed the economical convenience of different scenarios, so cryoEM scientists have a clearer picture of the setup that is best suited for their needs and budgets. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

TU-CD-304-11: Veritas 2.0: A Cloud-Based Tool to Facilitate Research and Innovation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishra, P; Patankar, A; Etmektzoglou, A

Purpose: We introduce Veritas 2.0, a cloud-based, non-clinical research portal, to facilitate translation of radiotherapy research ideas to new delivery techniques. The ecosystem of research tools includes web apps for a research beam builder for TrueBeam Developer Mode, an image reader for compressed and uncompressed XIM files, and a trajectory log file based QA/beam delivery analyzer. Methods: The research beam builder can generate TrueBeam readable XML file either from scratch or from pre-existing DICOM-RT plans. DICOM-RT plan is first converted to XML format and then researcher can interactively modify or add control points to them. Delivered beam can be verifiedmore » via reading generated images and analyzing trajectory log files. Image reader can read both uncompressed and HND-compressed XIM images. The trajectory log analyzer lets researchers plot expected vs. actual values and deviations among 30 mechanical axes. The analyzer gives an animated view of MLC patterns for the beam delivery. Veritas 2.0 is freely available and its advantages versus standalone software are i) No software installation or maintenance needed, ii) easy accessibility across all devices iii) seamless upgrades and iv) OS independence. Veritas is written using open-source tools like twitter bootstrap, jQuery, flask, and Python-based modules. Results: In the first experiment, an anonymized 7-beam DICOM-RT IMRT plan was converted to XML beam containing 1400 control points. kV and MV imaging points were inserted into this XML beam. In another experiment, a binary log file was analyzed to compare actual vs expected values and deviations among axes. Conclusions: Veritas 2.0 is a public cloud-based web app that hosts a pool of research tools for facilitating research from conceptualization to verification. It is aimed at providing a platform for facilitating research and collaboration. I am full time employee at Varian Medical systems, Palo Alto.« less

Limb darkening in Venus night-side disk as viewed from Akatsuki IR2

NASA Astrophysics Data System (ADS)

Satoh, Takehiko; Nakakushi, Takashi; Sato, Takao M.; Hashimoto, George L.

2017-10-01

Night-side hemisphere of Venus exhibits dark and bright regions as a result of spatially inhomogeneous cloud opacity which is illuminated by infrared radiation from deeper atmosphere. The 2-μm camera (IR2) onboard Akatsuki, Japan's Venus Climate Orbiter, is equipped with three narrow-band filters (1.735, 2.26, and 2.32 μm) to image Venus night-side disk in well-known transparency windows of CO2 atmosphere (Allen and Crawford 1984). In general, a cloud feature appears brightest when it is in the disk center and becomes darker as the zenith angle of emergent light increases. Such limb darkening was observed with Galileo/NIMS and mathematically approximated (Carlson et al., 1993). Limb-darkening correction helps to identify branches, in a 1.74-μm vs. 2.3-μm radiances scatter plot, each of which corresponds to a group of aerosols with similar properties. We analyzed Akatsuki/IR2 images to characterize the limb darkening for three night-side filters.There is, however, contamination from the intense day-side disk blurred by IR2's point spread function (PSF). It is found that infrared light can be multiplly reflected within the Si substrate of IR2 detector (1024x1024 pixels PtSi array), causing elongated tail in the actual PSF. We treated this in two different ways. One is to mathematically approximate the PSF (with a combination of modified Lorentz functions) and another is to differentiate 2.26-μm image from 2.32-μm image so that the blurred light pattern can directly be obtained. By comparing results from these two methods, we are able to reasonablly clean up the night-side images and limb darkening is extracted. Physical interpretation of limb darkening, as well as "true" time variations of cloud brightness will be presented/discussed.

ARC-1989-AC89-7009

NASA Image and Video Library

1989-08-21

This picture of Neptune was produced from images taken through the ultraviolet, violet and green filters of the Voyager 2 wide-angle camera. This 'false' color image has been made to show clearly details of the cloud structure and to paint clouds located at different altitudes with different colors. Dark, deeplying clouds tend to be masked in the ultraviolet wavelength since overlying air molecules are particularly effective in scattering sunlight there which brightens the sky above them. Such areas appear dark blue in this photo. The Great Dark Spot (GDS) and the high southern latitudes have a deep bluish cast in this image, indication they are regions where visible light (but not ultraviolet light) may penetrate to a deeper layer of dark cloud or haze in Neptune's atmosphere. Conversely, the pinkish clouds may be positioned at high altitudes.

Clouds

NASA Image and Video Library

2010-09-14

Clouds are common near the north polar caps throughout the spring and summer. The clouds typically cause a haze over the extensive dune fields. This image from NASA Mars Odyssey shows the edge of the cloud front.

NOAA-L satellite arrives at Vandenberg AFB

NASA Technical Reports Server (NTRS)

2000-01-01

A crated National Oceanic and Atmospheric Administration (NOAA-L) satellite is moved inside the B16-10 spacecraft processing hangar at Vandenberg Air Force Base, Calif. NOAA-L is part of the Polar- Orbiting Operational Environmental Satellite (POES) program that provides atmospheric measurements of temperature, humidity, ozone and cloud images, tracking weather patterns that affect the global weather and climate. The launch of the NOAA-L satellite is scheduled no earlier than Sept. 12 aboard a Lockheed Martin Titan II rocket. NOAA-L satellite arrives at Vandenberg AFB

NASA Technical Reports Server (NTRS)

2000-01-01

Inside the B16-10 spacecraft processing hangar at Vandenberg Air Force Base, Calif., workers oversee the uncrating of the National Oceanic and Atmospheric Administration (NOAA-L) satellite. NOAA-L is part of the Polar-Orbiting Operational Environmental Satellite (POES) program that provides atmospheric measurements of temperature, humidity, ozone and cloud images, tracking weather patterns that affect the global weather and climate. The launch of the NOAA-L satellite is scheduled no earlier than Sept. 12 aboard a Lockheed Martin Titan II rocket. KSC00vafbdig006

NASA Image and Video Library

2000-06-30

Inside the B16-10 spacecraft processing hangar at Vandenberg Air Force Base, Calif., workers oversee the mating of the Apogee Kick Motor (below) to the National Oceanic and Atmospheric Administration (NOAA-L) satellite above. NOAA-L is part of the Polar-Orbiting Operational Environmental Satellite (POES) program that provides atmospheric measurements of temperature, humidity, ozone and cloud images, tracking weather patterns that affect the global weather and climate. The launch of the NOAA-L satellite is scheduled no earlier than Sept. 12 aboard a Lockheed Martin Titan II rocket

KSC00vafbdig002

NASA Image and Video Library

2000-06-27

Outside the B16-10 spacecraft processing hangar at Vandenberg Air Force Base, Calif., a crated National Oceanic and Atmospheric Administration (NOAA-L) satellite is lowered to the ground before being moved inside. NOAA-L is part of the Polar-Orbiting Operational Environmental Satellite (POES) program that provides atmospheric measurements of temperature, humidity, ozone and cloud images, tracking weather patterns that affect the global weather and climate. The launch of the NOAA-L satellite is scheduled no earlier than Sept. 12 aboard a Lockheed Martin Titan II rocket

Selection of optical model of stereophotography experiment for determination the cloud base height as a problem of testing of statistical hypotheses

NASA Astrophysics Data System (ADS)

Chulichkov, Alexey I.; Nikitin, Stanislav V.; Emilenko, Alexander S.; Medvedev, Andrey P.; Postylyakov, Oleg V.

2017-10-01

Earlier, we developed a method for estimating the height and speed of clouds from cloud images obtained by a pair of digital cameras. The shift of a fragment of the cloud in the right frame relative to its position in the left frame is used to estimate the height of the cloud and its velocity. This shift is estimated by the method of the morphological analysis of images. However, this method requires that the axes of the cameras are parallel. Instead of real adjustment of the axes, we use virtual camera adjustment, namely, a transformation of a real frame, the result of which could be obtained if all the axes were perfectly adjusted. For such adjustment, images of stars as infinitely distant objects were used: on perfectly aligned cameras, images on both the right and left frames should be identical. In this paper, we investigate in more detail possible mathematical models of cloud image deformations caused by the misalignment of the axes of two cameras, as well as their lens aberration. The simplest model follows the paraxial approximation of lens (without lens aberrations) and reduces to an affine transformation of the coordinates of one of the frames. The other two models take into account the lens distortion of the 3rd and 3rd and 5th orders respectively. It is shown that the models differ significantly when converting coordinates near the edges of the frame. Strict statistical criteria allow choosing the most reliable model, which is as much as possible consistent with the measurement data. Further, each of these three models was used to determine parameters of the image deformations. These parameters are used to provide cloud images to mean what they would have when measured using an ideal setup, and then the distance to cloud is calculated. The results were compared with data of a laser range finder.

Jupiter's Northern Hemisphere in False Color (Time Set 2)

NASA Technical Reports Server (NTRS)

1997-01-01

Mosaic of Jupiter's northern hemisphere between 10 and 50 degrees latitude. Jupiter's atmospheric circulation is dominated by alternating eastward and westward jets from equatorial to polar latitudes. The direction and speed of these jets in part determine the color and texture of the clouds seen in this mosaic. Also visible are several other common Jovian cloud features, including large white ovals, bright spots, dark spots, interacting vortices, and turbulent chaotic systems. The north-south dimension of each of the two interacting vortices in the upper half of the mosaic is about 3500 kilometers.

This mosaic uses the Galileo imaging camera's three near-infrared wavelengths (756 nanometers, 727 nanometers, and 889 nanometers displayed in red, green, and blue) to show variations in cloud height and thickness. Light blue clouds are high and thin, reddish clouds are deep, and white clouds are high and thick. The clouds and haze over the ovals are high, extending into Jupiter's stratosphere. Dark purple most likely represents a high haze overlying a clear deep atmosphere. Galileo is the first spacecraft to distinguish cloud layers on Jupiter.

North is at the top. The images are projected on a sphere, with features being foreshortened towards the north. The smallest resolved features are tens of kilometers in size. These images were taken on April 3, 1997, at a range of 1.4 million kilometers by the Solid State Imaging system (CCD) on NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Cloud Detection by Fusing Multi-Scale Convolutional Features

NASA Astrophysics Data System (ADS)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

The Feasibility of 3d Point Cloud Generation from Smartphones

NASA Astrophysics Data System (ADS)

Alsubaie, N.; El-Sheimy, N.

2016-06-01

This paper proposes a new technique for increasing the accuracy of direct geo-referenced image-based 3D point cloud generated from low-cost sensors in smartphones. The smartphone's motion sensors are used to directly acquire the Exterior Orientation Parameters (EOPs) of the captured images. These EOPs, along with the Interior Orientation Parameters (IOPs) of the camera/ phone, are used to reconstruct the image-based 3D point cloud. However, because smartphone motion sensors suffer from poor GPS accuracy, accumulated drift and high signal noise, inaccurate 3D mapping solutions often result. Therefore, horizontal and vertical linear features, visible in each image, are extracted and used as constraints in the bundle adjustment procedure. These constraints correct the relative position and orientation of the 3D mapping solution. Once the enhanced EOPs are estimated, the semi-global matching algorithm (SGM) is used to generate the image-based dense 3D point cloud. Statistical analysis and assessment are implemented herein, in order to demonstrate the feasibility of 3D point cloud generation from the consumer-grade sensors in smartphones.

Vertical Optical Scanning with Panoramic Vision for Tree Trunk Reconstruction

PubMed Central

Berveglieri, Adilson; Liang, Xinlian; Honkavaara, Eija

2017-01-01

This paper presents a practical application of a technique that uses a vertical optical flow with a fisheye camera to generate dense point clouds from a single planimetric station. Accurate data can be extracted to enable the measurement of tree trunks or branches. The images that are collected with this technique can be oriented in photogrammetric software (using fisheye models) and used to generate dense point clouds, provided that some constraints on the camera positions are adopted. A set of images was captured in a forest plot in the experiments. Weighted geometric constraints were imposed in the photogrammetric software to calculate the image orientation, perform dense image matching, and accurately generate a 3D point cloud. The tree trunks in the scenes were reconstructed and mapped in a local reference system. The accuracy assessment was based on differences between measured and estimated trunk diameters at different heights. Trunk sections from an image-based point cloud were also compared to the corresponding sections that were extracted from a dense terrestrial laser scanning (TLS) point cloud. Cylindrical fitting of the trunk sections allowed the assessment of the accuracies of the trunk geometric shapes in both clouds. The average difference between the cylinders that were fitted to the photogrammetric cloud and those to the TLS cloud was less than 1 cm, which indicates the potential of the proposed technique. The point densities that were obtained with vertical optical scanning were 1/3 less than those that were obtained with TLS. However, the point density can be improved by using higher resolution cameras. PMID:29207468

Vertical Optical Scanning with Panoramic Vision for Tree Trunk Reconstruction.

PubMed

Berveglieri, Adilson; Tommaselli, Antonio M G; Liang, Xinlian; Honkavaara, Eija

2017-12-02

This paper presents a practical application of a technique that uses a vertical optical flow with a fisheye camera to generate dense point clouds from a single planimetric station. Accurate data can be extracted to enable the measurement of tree trunks or branches. The images that are collected with this technique can be oriented in photogrammetric software (using fisheye models) and used to generate dense point clouds, provided that some constraints on the camera positions are adopted. A set of images was captured in a forest plot in the experiments. Weighted geometric constraints were imposed in the photogrammetric software to calculate the image orientation, perform dense image matching, and accurately generate a 3D point cloud. The tree trunks in the scenes were reconstructed and mapped in a local reference system. The accuracy assessment was based on differences between measured and estimated trunk diameters at different heights. Trunk sections from an image-based point cloud were also compared to the corresponding sections that were extracted from a dense terrestrial laser scanning (TLS) point cloud. Cylindrical fitting of the trunk sections allowed the assessment of the accuracies of the trunk geometric shapes in both clouds. The average difference between the cylinders that were fitted to the photogrammetric cloud and those to the TLS cloud was less than 1 cm, which indicates the potential of the proposed technique. The point densities that were obtained with vertical optical scanning were 1/3 less than those that were obtained with TLS. However, the point density can be improved by using higher resolution cameras.

Cloud Size Distributions from Multi-sensor Observations of Shallow Cumulus Clouds

NASA Astrophysics Data System (ADS)

Kleiss, J.; Riley, E.; Kassianov, E.; Long, C. N.; Riihimaki, L.; Berg, L. K.

2017-12-01

Combined radar-lidar observations have been used for almost two decades to document temporal changes of shallow cumulus clouds at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Facility's Southern Great Plains (SGP) site in Oklahoma, USA. Since the ARM zenith-pointed radars and lidars have a narrow field-of-view (FOV), the documented cloud statistics, such as distributions of cloud chord length (or horizontal length scale), represent only a slice along the wind direction of a region surrounding the SGP site, and thus may not be representative for this region. To investigate this impact, we compare cloud statistics obtained from wide-FOV sky images collected by ground-based observations at the SGP site to those from the narrow FOV active sensors. The main wide-FOV cloud statistics considered are cloud area distributions of shallow cumulus clouds, which are frequently required to evaluate model performance, such as routine large eddy simulation (LES) currently being conducted by the ARM LASSO (LES ARM Symbiotic Simulation and Observation) project. We obtain complementary macrophysical properties of shallow cumulus clouds, such as cloud chord length, base height and thickness, from the combined radar-lidar observations. To better understand the broader observational context where these narrow FOV cloud statistics occur, we compare them to collocated and coincident cloud area distributions from wide-FOV sky images and high-resolution satellite images. We discuss the comparison results and illustrate the possibility to generate a long-term climatology of cloud size distributions from multi-sensor observations at the SGP site.

Smart cloud system with image processing server in diagnosing brain diseases dedicated for hospitals with limited resources.

PubMed

Fahmi, Fahmi; Nasution, Tigor H; Anggreiny, Anggreiny

2017-01-01

The use of medical imaging in diagnosing brain disease is growing. The challenges are related to the big size of data and complexity of the image processing. High standard of hardware and software are demanded, which can only be provided in big hospitals. Our purpose was to provide a smart cloud system to help diagnosing brain diseases for hospital with limited infrastructure. The expertise of neurologists was first implanted in cloud server to conduct an automatic diagnosis in real time using image processing technique developed based on ITK library and web service. Users upload images through website and the result, in this case the size of tumor was sent back immediately. A specific image compression technique was developed for this purpose. The smart cloud system was able to measure the area and location of tumors, with average size of 19.91 ± 2.38 cm2 and an average response time 7.0 ± 0.3 s. The capability of the server decreased when multiple clients accessed the system simultaneously: 14 ± 0 s (5 parallel clients) and 27 ± 0.2 s (10 parallel clients). The cloud system was successfully developed to process and analyze medical images for diagnosing brain diseases in this case for tumor.

The HEPiX Virtualisation Working Group: Towards a Grid of Clouds

NASA Astrophysics Data System (ADS)

Cass, Tony

2012-12-01

The use of virtual machine images, as for example with Cloud services such as Amazon's Elastic Compute Cloud, is attractive for users as they have a guaranteed execution environment, something that cannot today be provided across sites participating in computing grids such as the Worldwide LHC Computing Grid. However, Grid sites often operate within computer security frameworks which preclude the use of remotely generated images. The HEPiX Virtualisation Working Group was setup with the objective to enable use of remotely generated virtual machine images at Grid sites and, to this end, has introduced the idea of trusted virtual machine images which are guaranteed to be secure and configurable by sites such that security policy commitments can be met. This paper describes the requirements and details of these trusted virtual machine images and presents a model for their use to facilitate the integration of Grid- and Cloud-based computing environments for High Energy Physics.

Reconstruction of 3D Shapes of Opaque Cumulus Clouds from Airborne Multiangle Imaging: A Proof-of-Concept

NASA Astrophysics Data System (ADS)

Davis, A. B.; Bal, G.; Chen, J.

2015-12-01

Operational remote sensing of microphysical and optical cloud properties is invariably predicated on the assumption of plane-parallel slab geometry for the targeted cloud. The sole benefit of this often-questionable assumption about the cloud is that it leads to one-dimensional (1D) radiative transfer (RT)---a textbook, computationally tractable model. We present new results as evidence that, thanks to converging advances in 3D RT, inverse problem theory, algorithm implementation, and computer hardware, we are at the dawn of a new era in cloud remote sensing where we can finally go beyond the plane-parallel paradigm. Granted, the plane-parallel/1D RT assumption is reasonable for spatially extended stratiform cloud layers, as well as the smoothly distributed background aerosol layers. However, these 1D RT-friendly scenarios exclude cases that are critically important for climate physics. 1D RT---whence operational cloud remote sensing---fails catastrophically for cumuliform clouds that have fully 3D outer shapes and internal structures driven by shallow or deep convection. For these situations, the first order of business in a robust characterization by remote sensing is to abandon the slab geometry framework and determine the 3D geometry of the cloud, as a first step toward bone fide 3D cloud tomography. With this specific goal in mind, we deliver a proof-of-concept for an entirely new kind of remote sensing applicable to 3D clouds. It is based on highly simplified 3D RT and exploits multi-angular suites of cloud images at high spatial resolution. Airborne sensors like AirMSPI readily acquire such data. The key element of the reconstruction algorithm is a sophisticated solution of the nonlinear inverse problem via linearization of the forward model and an iteration scheme supported, where necessary, by adaptive regularization. Currently, the demo uses a 2D setting to show how either vertical profiles or horizontal slices of the cloud can be accurately reconstructed. Extension to 3D volumes is straightforward but the next challenge is to accommodate images at lower spatial resolution, e.g., from MISR/Terra. G. Bal, J. Chen, and A.B. Davis (2015). Reconstruction of cloud geometry from multi-angle images, Inverse Problems in Imaging (submitted).

Neural network cloud top pressure and height for MODIS

NASA Astrophysics Data System (ADS)

Håkansson, Nina; Adok, Claudia; Thoss, Anke; Scheirer, Ronald; Hörnquist, Sara

2018-06-01

Cloud top height retrieval from imager instruments is important for nowcasting and for satellite climate data records. A neural network approach for cloud top height retrieval from the imager instrument MODIS (Moderate Resolution Imaging Spectroradiometer) is presented. The neural networks are trained using cloud top layer pressure data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) dataset. Results are compared with two operational reference algorithms for cloud top height: the MODIS Collection 6 Level 2 height product and the cloud top temperature and height algorithm in the 2014 version of the NWC SAF (EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting) PPS (Polar Platform System). All three techniques are evaluated using both CALIOP and CPR (Cloud Profiling Radar for CloudSat (CLOUD SATellite)) height. Instruments like AVHRR (Advanced Very High Resolution Radiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) contain fewer channels useful for cloud top height retrievals than MODIS, therefore several different neural networks are investigated to test how infrared channel selection influences retrieval performance. Also a network with only channels available for the AVHRR1 instrument is trained and evaluated. To examine the contribution of different variables, networks with fewer variables are trained. It is shown that variables containing imager information for neighboring pixels are very important. The error distributions of the involved cloud top height algorithms are found to be non-Gaussian. Different descriptive statistic measures are presented and it is exemplified that bias and SD (standard deviation) can be misleading for non-Gaussian distributions. The median and mode are found to better describe the tendency of the error distributions and IQR (interquartile range) and MAE (mean absolute error) are found to give the most useful information of the spread of the errors. For all descriptive statistics presented MAE, IQR, RMSE (root mean square error), SD, mode, median, bias and percentage of absolute errors above 0.25, 0.5, 1 and 2 km the neural network perform better than the reference algorithms both validated with CALIOP and CPR (CloudSat). The neural networks using the brightness temperatures at 11 and 12 µm show at least 32 % (or 623 m) lower MAE compared to the two operational reference algorithms when validating with CALIOP height. Validation with CPR (CloudSat) height gives at least 25 % (or 430 m) reduction of MAE.

Towards 3D Matching of Point Clouds Derived from Oblique and Nadir Airborne Imagery

NASA Astrophysics Data System (ADS)

Zhang, Ming

Because of the low-expense high-efficient image collection process and the rich 3D and texture information presented in the images, a combined use of 2D airborne nadir and oblique images to reconstruct 3D geometric scene has a promising market for future commercial usage like urban planning or first responders. The methodology introduced in this thesis provides a feasible way towards fully automated 3D city modeling from oblique and nadir airborne imagery. In this thesis, the difficulty of matching 2D images with large disparity is avoided by grouping the images first and applying the 3D registration afterward. The procedure starts with the extraction of point clouds using a modified version of the RIT 3D Extraction Workflow. Then the point clouds are refined by noise removal and surface smoothing processes. Since the point clouds extracted from different image groups use independent coordinate systems, there are translation, rotation and scale differences existing. To figure out these differences, 3D keypoints and their features are extracted. For each pair of point clouds, an initial alignment and a more accurate registration are applied in succession. The final transform matrix presents the parameters describing the translation, rotation and scale requirements. The methodology presented in the thesis has been shown to behave well for test data. The robustness of this method is discussed by adding artificial noise to the test data. For Pictometry oblique aerial imagery, the initial alignment provides a rough alignment result, which contains a larger offset compared to that of test data because of the low quality of the point clouds themselves, but it can be further refined through the final optimization. The accuracy of the final registration result is evaluated by comparing it to the result obtained from manual selection of matched points. Using the method introduced, point clouds extracted from different image groups could be combined with each other to build a more complete point cloud, or be used as a complement to existing point clouds extracted from other sources. This research will both improve the state of the art of 3D city modeling and inspire new ideas in related fields.

HUBBLE SPOTS NORTHERN HEMISPHERIC CLOUDS ON URANUS

NASA Technical Reports Server (NTRS)

2002-01-01

Using visible light, astronomers for the first time this century have detected clouds in the northern hemisphere of Uranus. The newest images, taken July 31 and Aug. 1, 1997 with NASA Hubble Space Telescope's Wide Field and Planetary Camera 2, show banded structure and multiple clouds. Using these images, Dr. Heidi Hammel (Massachusetts Institute of Technology) and colleagues Wes Lockwood (Lowell Observatory) and Kathy Rages (NASA Ames Research Center) plan to measure the wind speeds in the northern hemisphere for the first time. Uranus is sometimes called the 'sideways' planet, because its rotation axis is tipped more than 90 degrees from the planet's orbit around the Sun. The 'year' on Uranus lasts 84 Earth years, which creates extremely long seasons - winter in the northern hemisphere has lasted for nearly 20 years. Uranus has also been called bland and boring, because no clouds have been detectable in ground-based images of the planet. Even to the cameras of the Voyager spacecraft in 1986, Uranus presented a nearly uniform blank disk, and discrete clouds were detectable only in the southern hemisphere. Voyager flew over the planet's cloud tops near the dead of northern winter (when the northern hemisphere was completely shrouded in darkness). Spring has finally come to the northern hemisphere of Uranus. The newest images, both the visible-wavelength ones described here and those taken a few days earlier with the Near Infrared and Multi-Object Spectrometer (NICMOS) by Erich Karkoschka (University of Arizona), show a planet with banded structure and detectable clouds. Two images are shown here. The 'aqua' image (on the left) is taken at 5,470 Angstroms, which is near the human eye's peak response to wavelength. Color has been added to the image to show what a person on a spacecraft near Uranus might see. Little structure is evident at this wavelength, though with image-processing techniques, a small cloud can be seen near the planet's northern limb (rightmost edge). The 'red' image (on the right) is taken at 6,190 Angstroms, and is sensitive to absorption by methane molecules in the planet's atmosphere. The banded structure of Uranus is evident, and the small cloud near the northern limb is now visible. Scientists are expecting that the discrete clouds and banded structure may become even more pronounced as Uranus continues in its slow pace around the Sun. 'Some parts of Uranus haven't seen the Sun in decades,' says Dr. Hammel, 'and historical records suggest that we may see the development of more banded structure and patchy clouds as the planet's year progresses.' Some scientists have speculated that the winds of Uranus are not symmetric around the planet's equator, but no clouds were visible to test those theories. The new data will provide the opportunity to measure the northern winds. Hammel and colleagues expect to have results soon. Credits: Heidi Hammel (Massachusetts Institute of Technology), and NASA.

SPHERE/ZIMPOL observations of the symbiotic system R Aquarii. I. Imaging of the stellar binary and the innermost jet clouds

NASA Astrophysics Data System (ADS)

Schmid, H. M.; Bazzon, A.; Milli, J.; Roelfsema, R.; Engler, N.; Mouillet, D.; Lagadec, E.; Sissa, E.; Sauvage, J.-F.; Ginski, C.; Baruffolo, A.; Beuzit, J. L.; Boccaletti, A.; Bohn, A. J.; Claudi, R.; Costille, A.; Desidera, S.; Dohlen, K.; Dominik, C.; Feldt, M.; Fusco, T.; Gisler, D.; Girard, J. H.; Gratton, R.; Henning, T.; Hubin, N.; Joos, F.; Kasper, M.; Langlois, M.; Pavlov, A.; Pragt, J.; Puget, P.; Quanz, S. P.; Salasnich, B.; Siebenmorgen, R.; Stute, M.; Suarez, M.; Szulágyi, J.; Thalmann, C.; Turatto, M.; Udry, S.; Vigan, A.; Wildi, F.

2017-06-01

Context. R Aqr is a symbiotic binary system consisting of a mira variable, a hot companion with a spectacular jet outflow, and an extended emission line nebula. Because of its proximity to the Sun, this object has been studied in much detail with many types of high resolution imaging and interferometric techniques. We have used R Aqr as test target for the visual camera subsystem ZIMPOL, which is part of the new extreme adaptive optics (AO) instrument SPHERE at the Very Large Telescope (VLT). Aims: We describe SPHERE/ZIMPOL test observations of the R Aqr system taken in Hα and other filters in order to demonstrate the exceptional performance of this high resolution instrument. We compare our observations with data from the Hubble Space Telescope (HST) and illustrate the complementarity of the two instruments. We use our data for a detailed characterization of the inner jet region of R Aqr. Methods: We analyze the high resolution ≈ 25 mas images from SPHERE/ZIMPOL and determine from the Hα emission the position, size, geometric structure, and line fluxes of the jet source and the clouds in the innermost region <2'' (<400 AU) of R Aqr. The data are compared to simultaneous HST line filter observations. The Hα fluxes and the measured sizes of the clouds yield Hα emissivities for many clouds from which one can derive the mean density, mass, recombination time scale, and other cloud parameters. Results: Our Hα data resolve for the first time the R Aqr binary and we measure for the jet source a relative position 45 mas West (position angle -89.5°) of the mira. The central jet source is the strongest Hα component with a flux of about 2.5 × 10-12 erg cm-2 s-1. North east and south west from the central source there are many clouds with very diverse structures. Within 0.5'' (100 AU) we see in the SW a string of bright clouds arranged in a zig-zag pattern and, further out, at 1''-2'', fainter and more extended bubbles. In the N and NE we see a bright, very elongated filamentary structure between 0.2''-0.7'' and faint perpendicular "wisps" further out. Some jet clouds are also detected in the ZIMPOL [O I] and He I filters, as well as in the HST-WFC3 line filters for Hα, [O III], [N II], and [O I]. We determine jet cloud parameters and find a very well defined correlation Ne ∝ r-1.3 between cloud density and distance to the central binary. Densities are very high with typical values of Ne ≈ 3 × 105 cm-3 for the "outer" clouds around 300 AU, Ne ≈ 3 × 106 cm-3 for the "inner" clouds around 50 AU, and even higher for the central jet source. The high Ne of the clouds implies short recombination or variability timescales of a year or shorter. Conclusions: Hα high resolution data provide a lot of diagnostic information for the ionized jet gas in R Aqr. Future Hα observations will provide the orientation of the orbital plane of the binary and allow detailed hydrodynamical investigations of this jet outflow and its interaction with the wind of the red giant companion. The reduced Hα image given in Fig. 6 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/602/A53

Orbiting Rainbows Simulation

NASA Image and Video Library

2015-04-22

This simulated image shows how a cloud of glitter in geostationary orbit would be illuminated and controlled by two laser beams. As the cloud orbits Earth, grains scatter the sun's light at different angles like many tiny prisms, similar to how rainbows are produced from light being dispersed by water droplets. That is why the project concept is called "Orbiting Rainbows." The cloud functions like a reflective surface, allowing the exoplanet (displayed in the bottom right) to be imaged. The orbit path is shown in the top right. On the bottom left, Earth's image is seen behind the cloud. To image an exoplanet, the cloud would need to have a diameter of nearly 98 feet (30 meters). This simulation confines the cloud to a 3.3 x 3.3 x 3.3 foot volume (1 x 1 x 1 meter volume) to simplify the computations. The elements of the orbiting telescope are not to scale. Orbiting Rainbows is currently in Phase II development through the NASA Innovative Advanced Concepts (NIAC) Program. It was one of five technology proposals chosen for continued study in 2014. In the current phase, Orbiting Rainbows researchers are conducting small-scale ground experiments to demonstrate how granular materials can be manipulated using lasers and simulations of how the imaging system would behave in orbit. http://photojournal.jpl.nasa.gov/catalog/PIA19318

International inter-rater agreement in scoring acne severity utilizing cloud-based image sharing of mobile phone photographs.

PubMed

Foolad, Negar; Ornelas, Jennifer N; Clark, Ashley K; Ali, Ifrah; Sharon, Victoria R; Al Mubarak, Luluah; Lopez, Andrés; Alikhan, Ali; Al Dabagh, Bishr; Firooz, Alireza; Awasthi, Smita; Liu, Yu; Li, Chin-Shang; Sivamani, Raja K

2017-09-01

Cloud-based image sharing technology allows facilitated sharing of images. Cloud-based image sharing technology has not been well-studied for acne assessments or treatment preferences, among international evaluators. We evaluated inter-rater variability of acne grading and treatment recommendations among an international group of dermatologists that assessed photographs. This is a prospective, single visit photographic study to assess inter-rater agreement of acne photographs shared through an integrated mobile device, cloud-based, and HIPAA-compliant platform. Inter-rater agreements for global acne assessment and acne lesion counts were evaluated by the Kendall's coefficient of concordance while correlations between treatment recommendations and acne severity were calculated by Spearman's rank correlation coefficient. There was good agreement for the evaluation of inflammatory lesions (KCC = 0.62, P < 0.0001), noninflammatory lesions (KCC = 0.62, P < 0.0001), and the global acne grading system score (KCC = 0.69, P < 0.0001). Topical retinoid, oral antibiotic, and isotretinoin treatment preferences correlated with photographic based acne severity. Our study supports the use of mobile phone based photography and cloud-based image sharing for acne assessment. Cloud-based sharing may facilitate acne care and research among international collaborators. © 2017 The International Society of Dermatology.

Lightweight Electronic Camera for Research on Clouds

NASA Technical Reports Server (NTRS)

Lawson, Paul

2006-01-01

"Micro-CPI" (wherein "CPI" signifies "cloud-particle imager") is the name of a small, lightweight electronic camera that has been proposed for use in research on clouds. It would acquire and digitize high-resolution (3- m-pixel) images of ice particles and water drops at a rate up to 1,000 particles (and/or drops) per second.

Tropical Storm Ernesto over Cuba

NASA Image and Video Library

2006-08-28

This infrared image shows Tropical Storm Ernesto over Cuba, from the Atmospheric Infrared Sounder AIRS on NASA Aqua satellite in August, 2006. Because infrared radiation does not penetrate through clouds, AIRS infrared images show either the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures (in purple) are associated with high, cold cloud tops that make up the top of the storm. In cloud-free areas the AIRS instrument will receive the infrared radiation from the surface of the Earth, resulting in the warmest temperatures (orange/red). http://photojournal.jpl.nasa.gov/catalog/PIA00510

Typhoon Ioke in the Western Pacific

NASA Image and Video Library

2006-08-29

This infrared image shows Typhoon Ioke in the Western Pacific, from the Atmospheric Infrared Sounder AIRS on NASA Aqua satellite in August, 2006. Because infrared radiation does not penetrate through clouds, AIRS infrared images show either the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures (in purple) are associated with high, cold cloud tops that make up the top of the storm. In cloud-free areas the AIRS instrument will receive the infrared radiation from the surface of the Earth, resulting in the warmest temperatures (orange/red). http://photojournal.jpl.nasa.gov/catalog/PIA00511

Hurricane Ileana in the Eastern Pacific

NASA Image and Video Library

2006-08-22

This is an infrared image of Hurricane Ileana in the Eastern Pacific, from the Atmospheric Infrared Sounder (AIRS) on NASA's Aqua satellite on August 22, 2006. This AIRS image shows the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures (in purple) are associated with high, cold cloud tops that make up the top of the storm. The infrared signal does not penetrate through clouds. Where there are no clouds the AIRS instrument reads the infrared signal from the surface of the Earth, revealing warmer temperatures (red). http://photojournal.jpl.nasa.gov/catalog/PIA00509

Hole punch clouds over the Bahamas

NASA Image and Video Library

2017-12-08

In elementary school, students learn that water freezes at 0 degrees Celsius (32 degrees Fahrenheit). That is true most of the time, but there are exceptions to the rule. For instance, water with very few impurities (such as dust or pollution particles, fungal spores, bacteria) can be chilled to much cooler temperatures and still remain liquid—a process known as supercooling. Supercooling may sound exotic, but it occurs pretty routinely in Earth’s atmosphere. Altocumulus clouds, a common type of mid-altitude cloud, are mostly composed of water droplets supercooled to a temperature of about -15 degrees C. Altocumulus clouds with supercooled tops cover about 8 percent of Earth’s surface at any given time. Supercooled water droplets play a key role in the formation of hole-punch and canal clouds, the distinctive clouds shown in these satellite images. Hole-punch clouds usually appear as circular gaps in decks of altocumulus clouds; canal clouds look similar but the gaps are longer and thinner. This true-color image shows hole-punch and canal clouds off the coast of Florida, as observed on December 12, 2014, by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. Both types of cloud form when aircraft fly through cloud decks rich with supercooled water droplets and produce aerodynamic contrails. Air expands and cools as it moves around the wings and past the propeller, a process known as adiabatic cooling. Air temperatures over jet wings often cool by as much as 20 degrees Celsius, pushing supercooled water droplets to the point of freezing. As ice crystals form, they absorb nearby water droplets. Since ice crystals are relatively heavy, they tend to sink. This triggers tiny bursts of snow or rain that leave gaps in the cloud cover. Whether a cloud formation becomes a hole-punch or canal depends on the thickness of the cloud layer, the air temperature, and the degree of horizontal wind shear. Both descending and ascending aircraft—including jets and propeller planes—can trigger hole-punch and canal clouds. The nearest major airports in the images above include Miami International, Fort Lauderdale International, Grand Bahama International, and Palm Beach International. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Cassini ISS and VIMS observations of Titan's north polar region during the T120 and T121 flybys: The Curious Case of the Clouds

NASA Astrophysics Data System (ADS)

Turtle, E. P.; Barnes, J. W.; Perry, J.; Barbara, J.; Hayes, A.; Corlies, P.; Kelland, J.; West, R. A.; Del Genio, A. D.; Soderblom, J. M.; McEwen, A. S.; Sotin, C.

2016-12-01

As northern summer approaches, atmospheric circulation models predict storm activity will pick up at Titan's high northern latitudes, as was observed at high southern latitudes upon Cassini's arrival during late southern summer in 2004. Cassini's Imaging Science Subsystem (ISS) and Visual and Infrared Mapping Spectrometer (VIMS) teams have been targeting Titan to document changes in weather patterns over the course of the mission, and there is particular interest in following the onset of clouds in the north polar region where Titan's lakes and seas are concentrated. The T120 and T121 flybys of Titan, on 7 June and 25 July 2016, respectively, provided views of high northern latitudes, and each instrument performed a series of observations over more than 24 hours during both flybys. Intriguingly, at first look the ISS and VIMS observations appear strikingly different from each other: in the ISS observations made during each flyby, surface features are apparent and only a few isolated clouds are detected; however, the VIMS observations suggest widespread cloud cover at high northern latitudes during both flybys. Although the instruments achieve different resolutions, that alone cannot explain the differences. The observations were made over the same time periods, so differences in illumination geometry or changes in the clouds themselves are also unlikely to be the cause for the apparent discrepancy; VIMS shows persistent atmospheric features over the entire observation period and ISS consistently detects surface features with just a few localized clouds. Clouds with low optical depth (lower than the optical depth of Titan's atmospheric haze at the same wavelength) might be more easily apparent at the longer wavelengths of the VIMS observations, which extend out to 5 µm (haze optical depth 0.2), compared to the ISS observations at 938 nm (haze optical depth 2). However, the lack of any apparent change in the visibility of lakes and seas in the ISS images compared to previous flybys where no clouds were observed is still difficult to explain. We will present our analyses of the sequences of observations made by ISS and VIMS during T120 and T121, as well as an ongoing ground-based observing campaign (including data from 8 June and 23 July), and the implications for the behavior of Titan's atmosphere leading up to northern summer.

Pillars and globules at the edges of H ii regions. Confronting Herschel observations and numerical simulations

NASA Astrophysics Data System (ADS)

Tremblin, P.; Minier, V.; Schneider, N.; Audit, E.; Hill, T.; Didelon, P.; Peretto, N.; Arzoumanian, D.; Motte, F.; Zavagno, A.; Bontemps, S.; Anderson, L. D.; André, Ph.; Bernard, J. P.; Csengeri, T.; Di Francesco, J.; Elia, D.; Hennemann, M.; Könyves, V.; Marston, A. P.; Nguyen Luong, Q.; Rivera-Ingraham, A.; Roussel, H.; Sousbie, T.; Spinoglio, L.; White, G. J.; Williams, J.

2013-12-01

Context. Herschel far-infrared imaging observations have revealed the density structure of the interface between H ii regions and molecular clouds in great detail. In particular, pillars and globules are present in many high-mass star-forming regions, such as the Eagle nebula (M 16) and the Rosette molecular cloud, and understanding their origin will help characterize triggered star formation. Aims: The formation mechanisms of these structures are still being debated. The initial morphology of the molecular cloud and its turbulent state are key parameters since they generate deformations and curvatures of the shell during the expansion of the H ii region. Recent numerical simulations have shown how pillars can arise from the collapse of the shell in on itself and how globules can be formed from the interplay of the turbulent molecular cloud and the ionization from massive stars. The goal here is to test this scenario through recent observations of two massive star-forming regions, M 16 and the Rosette molecular cloud. Methods: First, the column density structure of the interface between molecular clouds and associated H ii regions was characterized using column density maps obtained from far-infrared imaging of the Herschel HOBYS key programme. Then, the DisPerSe algorithm was used on these maps to detect the compressed layers around the ionized gas and pillars in different evolutionary states. Column density profiles were constructed. Finally, their velocity structure was investigated using CO data, and all observational signatures were tested against some distinct diagnostics established from simulations. Results: The column density profiles have revealed the importance of compression at the edge of the ionized gas. The velocity properties of the structures, i.e. pillars and globules, are very close to what we predict from the numerical simulations. We have identified a good candidate of a nascent pillar in the Rosette molecular cloud that presents the velocity pattern of the shell collapsing on itself, induced by a high local curvature. Globules have a bulk velocity dispersion that indicates the importance of the initial turbulence in their formation, as proposed from numerical simulations. Altogether, this study re-enforces the picture of pillar formation by shell collapse and globule formation by the ionization of highly turbulent clouds. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.

Cloud solution for histopathological image analysis using region of interest based compression.

PubMed

Kanakatte, Aparna; Subramanya, Rakshith; Delampady, Ashik; Nayak, Rajarama; Purushothaman, Balamuralidhar; Gubbi, Jayavardhana

2017-07-01

Recent technological gains have led to the adoption of innovative cloud based solutions in medical imaging field. Once the medical image is acquired, it can be viewed, modified, annotated and shared on many devices. This advancement is mainly due to the introduction of Cloud computing in medical domain. Tissue pathology images are complex and are normally collected at different focal lengths using a microscope. The single whole slide image contains many multi resolution images stored in a pyramidal structure with the highest resolution image at the base and the smallest thumbnail image at the top of the pyramid. Highest resolution image will be used for tissue pathology diagnosis and analysis. Transferring and storing such huge images is a big challenge. Compression is a very useful and effective technique to reduce the size of these images. As pathology images are used for diagnosis, no information can be lost during compression (lossless compression). A novel method of extracting the tissue region and applying lossless compression on this region and lossy compression on the empty regions has been proposed in this paper. The resulting compression ratio along with lossless compression on tissue region is in acceptable range allowing efficient storage and transmission to and from the Cloud.

Temporal Evolution of SL-9 Impact Sites on Jupiter and Global Maps of Jupiter from Multi-Observatory Visible and Infrared Images

NASA Technical Reports Server (NTRS)

Limaye, Sanjay S.

1996-01-01

The objective of this research was to investigate the temporal behavior of the impact features on Jupiter created by the fragments of the Shoemaker Levy-9 comet that collided with the planet in July 1994. The primary observations used in the study were ground based images of Jupiter acquired from the Swedish Solar Vacuum Tube on the island of La Palma in the Canary Islands. The measurement of position of the impact features in images acquired immediately after the impact over a period of a few days revealed that the apparent drift rates were too high and that a repetitive pattern could be seen in the longitude position on successive rotations. This could be explained only by the fact that the measured longitudes of the impact sites were being affected by parallax due to a significant elevation of the impact debris above the nominal cloud top altitude value used for image navigation. Once the apparent positions are analyzed as a function of the meridian angle, the parallax equation can be used to infer the height of the impact features above the cloud deck, once the true impact position (longitude) for the feature is known. Due to their inherent high spatial resolution, the HST measurements of the impact site locations have been accepted widely. However, these suffer from the parallax themselves since few of them were obtained at central meridian. Ground based imaging have the potential to improve this knowledge as they do observe most of the impact sites on either side of the central meridian, except for the degraded resolution. Measurements over a large number of images enables us to minimize the position error through regression and thus estimate both the actual impact site location devoid of parallax bias, and also of the altitude level of the impact debris above the cloud deck. With rapid imaging there is the potential to examine the time evolution of the altitude level. Several hundred ground based images were processed, navigated and subjected to the impact site location measurements. HST images were also acquired and used to calibrate the results and to improve the sample. The resources available enabled an in-depth study only of impact site A, however, many more images have since become available through the global network observations through Lowell Observatory.

Jupiter's Swirling Cloud Formations

NASA Image and Video Library

2018-02-15

See swirling cloud formations in the northern area of Jupiter's north temperate belt in this new view taken by NASA's Juno spacecraft. The color-enhanced image was taken on Feb. 7 at 5:42 a.m. PST (8:42 a.m. EST), as Juno performed its eleventh close flyby of Jupiter. At the time the image was taken, the spacecraft was about 5,086 miles (8,186 kilometers) from the tops of the clouds of the planet at a latitude of 39.9 degrees. Citizen scientist Kevin M. Gill processed this image using data from the JunoCam imager. https://photojournal.jpl.nasa.gov/catalog/PIA21978

Clouds and Ice of the Lambert-Amery System, East Antarctica

NASA Technical Reports Server (NTRS)

2002-01-01

These views from the Multi-angle Imaging SpectroRadiometer (MISR) illustrate ice surface textures and cloud-top heights over the Amery Ice Shelf/Lambert Glacier system in East Antarctica on October 25, 2002.

The left-hand panel is a natural-color view from MISR's downward-looking (nadir) camera. The center panel is a multi-angular composite from three MISR cameras, in which color acts as a proxy for angular reflectance variations related to texture. Here, data from the red-band of MISR's 60o forward-viewing, nadir and 60o backward-viewing cameras are displayed as red, green and blue, respectively. With this display technique, surfaces which predominantly exhibit backward-scattering (generally rough surfaces) appear red/orange, while surfaces which predominantly exhibit forward-scattering (generally smooth surfaces) appear blue. Textural variation for both the grounded and sea ice are apparent. The red/orange pixels in the lower portion of the image correspond with a rough and crevassed region near the grounding zone, that is, the area where the Lambert and four other smaller glaciers merge and the ice starts to float as it forms the Amery Ice Shelf. In the natural-color view, this rough ice is spectrally blue in color.

Clouds exhibit both forward and backward-scattering properties in the middle panel and thus appear purple, in distinct contrast with the underlying ice and snow. An additional multi-angular technique for differentiating clouds from ice is shown in the right-hand panel, which is a stereoscopically derived height field retrieved using automated pattern recognition involving data from multiple MISR cameras. Areas exhibiting insufficient spatial contrast for stereoscopic retrieval are shown in dark gray. Clouds are apparent as a result of their heights above the surface terrain. Polar clouds are an important factor in weather and climate. Inadequate characterization of cloud properties is currently responsible for large uncertainties in climate prediction models. Identification of polar clouds, mapping of their distributions, and retrieval of their heights provide information that will help to reduce this uncertainty.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire Earth between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 15171. The panels cover an area of 380 kilometers x 984 kilometers, and utilize data from blocks 145 to 151 within World Reference System-2 path 127.

MISR was built and is managed by NASA's Jet Propulsion Laboratory,Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center,Greenbelt, MD. JPL is a division of the California Institute of Technology.

Jupiter With Great Red Spot, Near Infrared, May 2017

NASA Image and Video Library

2017-06-30

This composite, false-color infrared image of Jupiter reveals haze particles over a range of altitudes, as seen in reflected sunlight. It was taken using the Gemini North Telescope's Near-InfraRed Imager (NIRI) on May 18, 2017, in collaboration with the investigation of Jupiter by NASA's Juno mission. Juno completed its sixth close approach to Jupiter a few hours after this observation. The multiple filters corresponding to each color used in the image cover wavelengths between 1.69 microns and 2.275 microns. Jupiter's Great Red Spot (GRS) appears as the brightest (white) region at these wavelengths, which are primarily sensitive to high-altitude clouds and hazes near and above the top of Jupiter's convective region. The GRS is one of the highest-altitude features in Jupiter's atmosphere. Narrow spiral streaks that appear to lead into it or out of it from surrounding regions probably represent atmospheric features being stretched by the intense winds within the GRS, such as the hook-like structure on its western edge (left side). Some are being swept off its eastern edge (right side) and into an extensive wave-like flow pattern, and there is even a trace of flow from its northern edge. Other features near the GRS include the dark block and dark oval to the south and the north of the eastern flow pattern, respectively, indicating a lower density of cloud and haze particles in those locations. Both are long-lived cyclonic circulations, rotating clockwise -- in the opposite direction as the counterclockwise rotation of the GRS. A prominent wave pattern is evident north of the equator, along with two bright ovals, which are anticyclones that appeared in January 2017. Both the wave pattern and the ovals may be associated with an impressive upsurge in stormy activity that has been observed in these latitudes this year. Another bright anticyclonic oval is seen further north. The Juno spacecraft may pass over these ovals, as well as the Great Red Spot, during its close approach to Jupiter on July 10, 2017, Pacific Time (July 11, Universal Time). High hazes are evident over both polar regions with much spatial structure not previously been seen quite so clearly in ground-based images The filters used for observations combined into this image admit infrared light centered on the following infrared wavelengths (and presented here in these colors): 1.69 microns (blue), 2.045 microns (cyan), 2.169 microns (green), 2.124 microns https://photojournal.jpl.nasa.gov/catalog/PIA21713

Large-scale Fractal Motion of Clouds

NASA Image and Video Library

2011-04-20

NASA image acquired September 15, 1999 This Landsat 7 image of clouds off the Chilean coast near the Juan Fernandez Islands (also known as the Robinson Crusoe Islands) on September 15, 1999, shows a unique pattern called a “von Karman vortex street.” This pattern has long been studied in the laboratory, where the vortices are created by oil flowing past a cylindrical obstacle, making a string of vortices only several tens of centimeters long. Study of this classic “flow past a circular cylinder” has been very important in the understanding of laminar and turbulent fluid flow that controls a wide variety of phenomena, from the lift under an aircraft wing to Earth’s weather. Here, the cylinder is replaced by Alejandro Selkirk Island (named after the true “Robinson Crusoe,” who was stranded here for many months in the early 1700s). The island is about 1.5 km in diameter, and rises 1.6 km into a layer of marine stratocumulus clouds. This type of cloud is important for its strong cooling of the Earth’s surface, partially counteracting the Greenhouse warming. An extended, steady equatorward wind creates vortices with clockwise flow off the eastern edge and counterclockwise flow off the western edge of the island. The vortices grow as they advect hundreds of kilometers downwind, making a street 10,000 times longer than those made in the laboratory. Observing the same phenomenon extended over such a wide range of sizes dramatizes the “fractal” nature of atmospheric convection and clouds. Fractals are characteristic of fluid flow and other dynamic systems that exhibit “chaotic” motions. Both clockwise and counter-clockwise vortices are generated by flow around the island. As the flow separates from the island’s leeward (away from the source of the wind) side, the vortices “swallow” some of the clear air over the island. (Much of the island air is cloudless due to a local “land breeze” circulation set up by the larger heat capacity of the waters surrounding the island.) The “swallowed” gulps of clear island air get carried along within the vortices, but these are soon mixed into the surrounding clouds. Landsat is unique in its ability to image both the small-scale eddies that mix clear and cloudy air, down to the 30 meter pixel size of Landsat, but also having a wide enough field-of-view, 180 km, to reveal the connection of the turbulence to large-scale flows such as the subtropical oceanic gyres. Landsat 7, with its new onboard digital recorder, has extended this capability away from the few Landsat ground stations to remote areas such as Alejandro Island, and thus is gradually providing a global dynamic picture of evolving human-scale phenomena. For more details on von Karman vortices, refer to climate.gsfc.nasa.gov/~cahalan. Image and caption courtesy Bob Cahalan, NASA GSFC Instrument: Landsat 7 - ETM+ Credit: NASA/GSFC/Landsat NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Join us on Facebook

Variability in modeled cloud feedback tied to differences in the climatological spatial pattern of clouds

NASA Astrophysics Data System (ADS)

Siler, Nicholas; Po-Chedley, Stephen; Bretherton, Christopher S.

2018-02-01

Despite the increasing sophistication of climate models, the amount of surface warming expected from a doubling of atmospheric CO_2 (equilibrium climate sensitivity) remains stubbornly uncertain, in part because of differences in how models simulate the change in global albedo due to clouds (the shortwave cloud feedback). Here, model differences in the shortwave cloud feedback are found to be closely related to the spatial pattern of the cloud contribution to albedo (α) in simulations of the current climate: high-feedback models exhibit lower (higher) α in regions of warm (cool) sea-surface temperatures, and therefore predict a larger reduction in global-mean α as temperatures rise and warm regions expand. The spatial pattern of α is found to be strongly predictive (r=0.84) of a model's global cloud feedback, with satellite observations indicating a most-likely value of 0.58± 0.31 Wm^{-2} K^{-1} (90% confidence). This estimate is higher than the model-average cloud feedback of 0.43 Wm^{-2} K^{-1}, with half the range of uncertainty. The observational constraint on climate sensitivity is weaker but still significant, suggesting a likely value of 3.68 ± 1.30 K (90% confidence), which also favors the upper range of model estimates. These results suggest that uncertainty in model estimates of the global cloud feedback may be substantially reduced by ensuring a realistic distribution of clouds between regions of warm and cool SSTs in simulations of the current climate.

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 2: Retrieval method and applications (report version)

NASA Technical Reports Server (NTRS)

Olson, William S.

1990-01-01

A physical retrieval method for estimating precipitating water distributions and other geophysical parameters based upon measurements from the DMSP-F8 SSM/I is developed. Three unique features of the retrieval method are (1) sensor antenna patterns are explicitly included to accommodate varying channel resolution; (2) precipitation-brightness temperature relationships are quantified using the cloud ensemble/radiative parameterization; and (3) spatial constraints are imposed for certain background parameters, such as humidity, which vary more slowly in the horizontal than the cloud and precipitation water contents. The general framework of the method will facilitate the incorporation of measurements from the SSMJT, SSM/T-2 and geostationary infrared measurements, as well as information from conventional sources (e.g., radiosondes) or numerical forecast model fields.

Fluorescence molecular imaging system with a novel mouse surface extraction method and a rotary scanning scheme

NASA Astrophysics Data System (ADS)

Zhao, Yue; Zhu, Dianwen; Baikejiang, Reheman; Li, Changqing

2015-03-01

We have developed a new fluorescence molecular tomography (FMT) imaging system, in which we utilized a phase shifting method to extract the mouse surface geometry optically and a rotary laser scanning approach to excite fluorescence molecules and acquire fluorescent measurements on the whole mouse body. Nine fringe patterns with a phase shifting of 2π/9 are projected onto the mouse surface by a projector. The fringe patterns are captured using a webcam to calculate a phase map that is converted to the geometry of the mouse surface with our algorithms. We used a DigiWarp approach to warp a finite element mesh of a standard digital mouse to the measured mouse surface thus the tedious and time-consuming procedure from a point cloud to mesh is avoided. Experimental results indicated that the proposed method is accurate with errors less than 0.5 mm. In the FMT imaging system, the mouse is placed inside a conical mirror and scanned with a line pattern laser that is mounted on a rotation stage. After being reflected by the conical mirror, the emitted fluorescence photons travel through central hole of the rotation stage and the band pass filters in a motorized filter wheel, and are collected by a CCD camera. Phantom experimental results of the proposed new FMT imaging system can reconstruct the target accurately.

Jupiter: New estimates of mean zonal flow at the cloud level

NASA Technical Reports Server (NTRS)

Limaye, Sanjay S.

1986-01-01

In order to reexamine the magnitude differences of the Jovian atmosphere's jets, as determined by Voyager 1 and 2 images, a novel approach is used to ascertain the zonal mean east-west component of motion. This technique is based on digital pattern matching, and is applied on pairs of mapped images to yield a profile of the mean zonal component that reproduces the exact locations of the easterly and westerly jets between + and 60 deg latitude. Results were obtained for all of the Voyager 1 and 2 cylindrical mosaics; the correlation coefficient between Voyagers 1 and 2 in mean zonal flow between + and - 60 deg latitude, determined from violet filter mosaics, is 0.998.

E4 True and False Color Hot Spot Mosaic

NASA Image and Video Library

1998-03-06

True and false color views of Jupiter from NASA's Galileo spacecraft show an equatorial "hotspot" on Jupiter. These images cover an area 34,000 kilometers by 11,000 kilometers (about 21,100 by 6,800 miles). The top mosaic combines the violet and near infrared continuum filter images to create an image similar to how Jupiter would appear to human eyes. Differences in coloration are due to the composition and abundances of trace chemicals in Jupiter's atmosphere. The bottom mosaic uses Galileo's three near-infrared wavelengths displayed in red, green, and blue) to show variations in cloud height and thickness. Bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the deep cloud with an overlying thin haze. The light blue region to the left is covered by a very high haze layer. The multicolored region to the right has overlapping cloud layers of different heights. Galileo is the first spacecraft to distinguish cloud layers on Jupiter. North is at the top. The mosaic covers latitudes 1 to 10 degrees and is centered at longitude 336 degrees west. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers (about 930,000 miles) by the Solid State Imaging camera system aboard Galileo. http://photojournal.jpl.nasa.gov/catalog/PIA00602

Evaluating the spatio-temporal performance of sky imager based solar irradiance analysis and forecasts

NASA Astrophysics Data System (ADS)

Schmidt, T.; Kalisch, J.; Lorenz, E.; Heinemann, D.

2015-10-01

Clouds are the dominant source of variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the world-wide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a shortest-term global horizontal irradiance (GHI) forecast experiment based on hemispheric sky images. A two month dataset with images from one sky imager and high resolutive GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series in different cloud scenarios. Overall, the sky imager based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depend strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1-2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

Hurricane Hector in the Eastern Pacific

NASA Image and Video Library

2006-08-17

Infrared, microwave, and visible/near-infrared images of Hurricane Hector in the eastern Pacific were created with data from the Atmospheric Infrared Sounder (AIRS) on NASA's Aqua satellite on August 17, 2006. The infrared AIRS image shows the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures (in purple) are associated with high, cold cloud tops that make up the top of the hurricane. The infrared signal does not penetrate through clouds. Where there are no clouds the AIRS instrument reads the infrared signal from the surface of the Earth, revealing warmer temperatures (red). At the time the data were taken from which these images were made, Hector is a well organized storm, with the strongest convection in the SE quadrant. The increasing vertical wind shear in the NW quadrant is appearing to have an effect. Maximum sustained winds are at 85 kt, gusts to 105 kt. Estimated minimum central pressure is 975 mbar. The microwave image is created from microwave radiation emitted by Earth's atmosphere and received by the instrument. It shows where the heaviest rainfall is taking place (in blue) in the storm. Blue areas outside of the storm where there are either some clouds or no clouds, indicate where the sea surface shines through. The "visible" image is created from data acquired by the visible light/near-infrared sensor on the AIRS instrument. http://photojournal.jpl.nasa.gov/catalog/PIA00507

Featured Image: A Molecular Cloud Outside Our Galaxy

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2018-06-01

What do molecular clouds look like outside of our own galaxy? See for yourself in the images above and below of N55, a molecular cloud located in the Large Magellanic Cloud (LMC). In a recent study led by Naslim Neelamkodan (Academia Sinica Institute of Astronomy and Astrophysics, Taiwan), a team of scientists explore N55 to determine how its cloud properties differ from clouds within the Milky Way. The image above reveals the distribution of infrared-emitting gas and dust observed in three bands by the Spitzer Space Telescope. Overplotted in cyan are observations from the Atacama Submillimeter Telescope Experiment tracing the clumpy, warm molecular gas. Below, new observations from the Atacama Large Millimeter/submillimeter Array (ALMA) reveal the sub-parsec-scale molecular clumps in greater detail, showing the correlation of massive clumps with Spitzer-identified young stellar objects (crosses). The study presented here indicates that this cloud in the LMC is the site of massive star formation, with properties similar to equivalent clouds in the Milky Way. To learn more about the authors findings, check out the article linked below.CitationNaslim N. et al 2018 ApJ 853 175. doi:10.3847/1538-4357/aaa5b0

Verifying Air Force Weather Passive Satellite Derived Cloud Analysis Products

NASA Astrophysics Data System (ADS)

Nobis, T. E.

2017-12-01

Air Force Weather (AFW) has developed an hourly World-Wide Merged Cloud Analysis (WWMCA) using imager data from 16 geostationary and polar-orbiting satellites. The analysis product contains information on cloud fraction, height, type and various optical properties including optical depth and integrated water path. All of these products are derived using a suite of algorithms which rely exclusively on passively sensed data from short, mid and long wave imager data. The system integrates satellites with a wide-range of capabilities, from the relatively simple two-channel OLS imager to the 16 channel ABI/AHI to create a seamless global analysis in real time. Over the last couple of years, AFW has started utilizing independent verification data from active sensed cloud measurements to better understand the performance limitations of the WWMCA. Sources utilized include space based lidars (CALIPSO, CATS) and radar (CloudSat) as well as ground based lidars from the Department of Energy ARM sites and several European cloud radars. This work will present findings from our efforts to compare active and passive sensed cloud information including comparison techniques/limitations as well as performance of the passive derived cloud information against the active.

A Jovian Hotspot in True and False Colors (Time set 1)

NASA Technical Reports Server (NTRS)

1997-01-01

True and false color views of an equatorial 'hotspot' on Jupiter. These images cover an area 34,000 kilometers by 11,000 kilometers. The top mosaic combines the violet (410 nanometers or nm) and near-infrared continuum (756 nm) filter images to create an image similar to how Jupiter would appear to human eyes. Differences in coloration are due to the composition and abundances of trace chemicals in Jupiter's atmosphere. The bottom mosaic uses Galileo's three near-infrared wavelengths (756 nm, 727 nm, and 889 nm displayed in red, green, and blue) to show variations in cloud height and thickness. Bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the deep cloud with an overlying thin haze. The light blue region to the left is covered by a very high haze layer. The multicolored region to the right has overlapping cloud layers of different heights. Galileo is the first spacecraft to distinguish cloud layers on Jupiter.

North is at the top. The mosaics cover latitudes 1 to 10 degrees and are centered at longitude 336 degrees West. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers by the Solid State Imaging system aboard NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

An efficient cloud detection method for high resolution remote sensing panchromatic imagery

NASA Astrophysics Data System (ADS)

Li, Chaowei; Lin, Zaiping; Deng, Xinpu

2018-04-01

In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.

Mystery #21

Atmospheric Science Data Center

2013-04-22

article title:  MISR Mystery Image Quiz #21   ... This mystery concerns a particular type of cloud, one example of which was imaged by the Multi-angle Imaging SpectroRadiometer (MISR) ... ) These clouds are commonly tracked using propeller-driven research aircraft. 3.   Two of these statements are false. Which one is ...

Two Methods for Retrieving UV Index for All Cloud Conditions from Sky Imager Products or Total SW Radiation Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Badosa, Jordi; Calbo, J.; McKenzie, R. L.

2014-07-01

In the present study, we assess the cloud effects on UV Index (UVI) and total solar radiation (TR) as a function of cloud cover estimations and sunny conditions (from sky imaging products) as well as of solar zenith angle (SZA). These analyses are undertaken for a southern-hemisphere mid-latitude site where a 10-years dataset is available. It is confirmed that clouds reduce TR more than UV, in particular for obscured Sun conditions, low cloud fraction (< 60%) and large SZA (> 60º). Similarly, clouds enhance TR more than UV, mainly for visible Sun conditions, large cloud fraction and large SZA. Twomore » methods to estimate UVI are developed: 1) from sky imaging cloud cover and sunny conditions, and 2) from TR measurements. Both methods may be used in practical operational applications, although Method 2 shows overall the best performance, since TR allows accounting for cloud optical properties. The mean absolute differences of Method 2 estimations with respect to measured values are 0.17 UVI units (for 1-minute data) and 0.79 Standard Erythemal Dose (SED) units (for daily integrations). Method 1 shows less accurate results but it is still suitable to estimate UVI: mean absolute differences are 0.37 UVI units and 1.6 SED.« less

Ship Tracks in the Sky

NASA Technical Reports Server (NTRS)

2002-01-01

Because clouds represent an area of great uncertainty in studies of global climate, scientists are interested in better understanding the processes by which clouds form and change over time. In recent years, scientists have turned their attention to the ways in which human-produced aerosol pollution modifies clouds. One area that has drawn scientists' attention is 'ship tracks,' or clouds that form from the sulfate aerosols released by large ships. Although ships are not significant sources of pollution themselves, they do release enough sulfur dioxide in the exhaust from their smokestacks to modify overlying clouds. Specifically, the aerosol particles formed by the ship exhaust in the atmosphere cause the clouds to be more reflective, carry more water, and possibly inhibit them from precipitating. This is one example of how humans have been creating and modifying clouds for generations through the burning of fossil fuels. This image was acquired over the northern Pacific Ocean by the Moderate-resolution Imaging Spectroradiometer (MODIS), flying aboard NASA's Terra satellite, on April 29, 2002. Image courtesy Jacques Descloitres, MODIS Land Rapid Response Team at NASA GSFC

Research on cloud background infrared radiation simulation based on fractal and statistical data

NASA Astrophysics Data System (ADS)

Liu, Xingrun; Xu, Qingshan; Li, Xia; Wu, Kaifeng; Dong, Yanbing

2018-02-01

Cloud is an important natural phenomenon, and its radiation causes serious interference to infrared detector. Based on fractal and statistical data, a method is proposed to realize cloud background simulation, and cloud infrared radiation data field is assigned using satellite radiation data of cloud. A cloud infrared radiation simulation model is established using matlab, and it can generate cloud background infrared images for different cloud types (low cloud, middle cloud, and high cloud) in different months, bands and sensor zenith angles.

Automated detection of cloud and cloud-shadow in single-date Landsat imagery using neural networks and spatial post-processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hughes, Michael J.; Hayes, Daniel J

2014-01-01

Use of Landsat data to answer ecological questions is contingent on the effective removal of cloud and cloud shadow from satellite images. We develop a novel algorithm to identify and classify clouds and cloud shadow, \\textsc{sparcs}: Spacial Procedures for Automated Removal of Cloud and Shadow. The method uses neural networks to determine cloud, cloud-shadow, water, snow/ice, and clear-sky membership of each pixel in a Landsat scene, and then applies a set of procedures to enforce spatial rules. In a comparison to FMask, a high-quality cloud and cloud-shadow classification algorithm currently available, \\textsc{sparcs} performs favorably, with similar omission errors for cloudsmore » (0.8% and 0.9%, respectively), substantially lower omission error for cloud-shadow (8.3% and 1.1%), and fewer errors of commission (7.8% and 5.0%). Additionally, textsc{sparcs} provides a measure of uncertainty in its classification that can be exploited by other processes that use the cloud and cloud-shadow detection. To illustrate this, we present an application that constructs obstruction-free composites of images acquired on different dates in support of algorithms detecting vegetation change.« less

Cat-Eyed Saturn

NASA Image and Video Library

2006-04-13

Bright, high altitude clouds, like those imaged here, often appear more filamentary or streak-like than clouds imaged at slightly deeper levels in Saturn atmosphere. This view also shows one of the many cat eye vortices.

Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

NASA Technical Reports Server (NTRS)

Bedka, Kristopher M.; Dworak, Richard; Brunner, Jason; Feltz, Wayne

2012-01-01

Two satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-mm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD.0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.

High-resolution photography of clouds from the surface: Retrieval of optical depth of thin clouds down to centimeter scales: High-Resolution Photography of Clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schwartz, Stephen E.; Huang, Dong; Vladutescu, Daniela Viviana

This article describes the approach and presents initial results, for a period of several minutes in north central Oklahoma, of an examination of clouds by high resolution digital photography from the surface looking vertically upward. A commercially available camera having 35-mm equivalent focal length up to 1200 mm (nominal resolution as fine as 6 µrad, which corresponds to 9 mm for cloud height 1.5 km) is used to obtain a measure of zenith radiance of a 30 m × 30 m domain as a two-dimensional image consisting of 3456 × 3456 pixels (12 million pixels). Downwelling zenith radiance varies substantiallymore » within single images and between successive images obtained at 4-s intervals. Variation in zenith radiance found on scales down to about 10 cm is attributed to variation in cloud optical depth (COD). Attention here is directed primarily to optically thin clouds, COD less than about 2. A radiation transfer model used to relate downwelling zenith radiance to COD and to relate the counts in the camera image to zenith radiance, permits determination of COD on a pixel-by-pixel basis. COD for thin clouds determined in this way exhibits considerable variation, for example, an order of magnitude within 15 m, a factor of 2 within 4 m, and 25% (0.12 to 0.15) over 14 cm. In conclusion, this approach, which examines cloud structure on scales 3 to 5 orders of magnitude finer than satellite products, opens new avenues for examination of cloud structure and evolution.« less

High-resolution photography of clouds from the surface: Retrieval of optical depth of thin clouds down to centimeter scales: High-Resolution Photography of Clouds

DOE PAGES

Schwartz, Stephen E.; Huang, Dong; Vladutescu, Daniela Viviana

2017-03-08

This article describes the approach and presents initial results, for a period of several minutes in north central Oklahoma, of an examination of clouds by high resolution digital photography from the surface looking vertically upward. A commercially available camera having 35-mm equivalent focal length up to 1200 mm (nominal resolution as fine as 6 µrad, which corresponds to 9 mm for cloud height 1.5 km) is used to obtain a measure of zenith radiance of a 30 m × 30 m domain as a two-dimensional image consisting of 3456 × 3456 pixels (12 million pixels). Downwelling zenith radiance varies substantiallymore » within single images and between successive images obtained at 4-s intervals. Variation in zenith radiance found on scales down to about 10 cm is attributed to variation in cloud optical depth (COD). Attention here is directed primarily to optically thin clouds, COD less than about 2. A radiation transfer model used to relate downwelling zenith radiance to COD and to relate the counts in the camera image to zenith radiance, permits determination of COD on a pixel-by-pixel basis. COD for thin clouds determined in this way exhibits considerable variation, for example, an order of magnitude within 15 m, a factor of 2 within 4 m, and 25% (0.12 to 0.15) over 14 cm. In conclusion, this approach, which examines cloud structure on scales 3 to 5 orders of magnitude finer than satellite products, opens new avenues for examination of cloud structure and evolution.« less

ARC-1990-AC91-2005

NASA Image and Video Library

1990-02-10

Range : 60,000 miles This image is a false-color version of a near- infrared map of lower-level clouds on the night side of Venus, obtained by the Near Infrared Mapping Spectrometer aboard Galileo. Taken at an infrared wavelength of 2.3 microns (about three times the longest wavelength visible to the human eye) the map shows the turbulent, cloudy middle atmosphere some 30-33 miles above the surface, 6-10 miles below the visible cloudtops. The image shows the radiant heat from the lower atmosphere (about 400 degrees F) shining through the sulfuric acid clouds, which appear as much as 10 times darker than the bright gaps between clouds. The colors indicate relative cloud transparency; white and red show thin cloud regions, while black and blue represent relatively this clouds. This cloud layer is at about 170 degrees F., at a pressure about 1/2 Earth's atmospheric pressure. About 2/3 of the dark hemisphere is visible, centered on longitude 350 West, with bright slivers of daylit high clouds visible at top and bottom left. Near the equator, the clouds appear fluffy and blocky; farther north, they are stretched out into East-West filaments by winds estimated at more than 150 mph, while the poles are capped by thick clouds at this altitude. The Near Infrared Mapping Spectrometer (NIMS) on the Galileo is a combined mapping (imaging) and spectral instrument. It can sense 408 contiguous wavelengths from 0.7 microns (deep red) to 5.2 microns, and can construct a map or image by mechanical scanning. It can spectroscopic-ally analyze atmospheres and surfaces and construct thermal and chemical maps. Designed and operated by scientists and engineers at the JPL, NIMS involves 15 scientists in the US, England and France.

Hubble Spots Northern Hemispheric Clouds on Uranus

NASA Technical Reports Server (NTRS)

1997-01-01

Using visible light, astronomers for the first time this century have detected clouds in the northern hemisphere of Uranus. The newest images, taken July 31 and Aug. 1, 1997 with NASA Hubble Space Telescope's Wide Field and Planetary Camera 2, show banded structure and multiple clouds. Using these images, Dr. Heidi Hammel (Massachusetts Institute of Technology) and colleagues Wes Lockwood (Lowell Observatory) and Kathy Rages (NASA Ames Research Center) plan to measure the wind speeds in the northern hemisphere for the first time.

Uranus is sometimes called the 'sideways' planet, because its rotation axis tipped more than 90 degrees from the planet's orbit around the Sun. The 'year' on Uranus lasts 84 Earth years, which creates extremely long seasons - winter in the northern hemisphere has lasted for nearly 20 years. Uranus has also been called bland and boring, because no clouds have been detectable in ground-based images of the planet. Even to the cameras of the Voyager spacecraft in 1986, Uranus presented a nearly uniform blank disk, and discrete clouds were detectable only in the southern hemisphere. Voyager flew over the planet's cloud tops near the dead of northern winter (when the northern hemisphere was completely shrouded in darkness).

Spring has finally come to the northern hemisphere of Uranus. The newest images, both the visible-wavelength ones described here and those taken a few days earlier with the Near Infrared and Multi-Object Spectrometer (NICMOS) by Erich Karkoschka (University of Arizona), show a planet with banded structure and detectable clouds.

Two images are shown here. The 'aqua' image (on the left) is taken at 5,470 Angstroms, which is near the human eye's peak response to wavelength. Color has been added to the image to show what a person on a spacecraft near Uranus might see. Little structure is evident at this wavelength, though with image-processing techniques, a small cloud can be seen near the planet's northern limb (rightmost edge). The 'red' image (on the right) is taken at 6,190 Angstroms, and is sensitive to absorption by methane molecules in the planet's atmosphere. The banded structure of Uranus is evident, and the small cloud near the northern limb is now visible.

Scientists are expecting that the discrete clouds and banded structure may become even more pronounced as Uranus continues in its slow pace around the Sun. 'Some parts of Uranus haven't seen the Sun in decades,' says Dr. Hammel, 'and historical records suggest that we may see the development of more banded structure and patchy clouds as the planet's year progresses.'

Some scientists have speculated that the winds of Uranus are not symmetric around the planet's equator, but no clouds were visible to test those theories. The new data will provide the opportunity to measure the northern winds. Hammel and colleagues expect to have results soon.

The Wide Field/Planetary Camera 2 was developed by the Jet Propulsion Laboratory and managed by the Goddard Spaced Flight Center for NASA's Office of Space Science.

This image and other images and data received from the Hubble Space Telescope are posted on the World Wide Web on the Space Telescope Science Institute home page at URL http:// oposite.stsci.edu/pubinfo/

How consistent are precipitation patterns predicted by GCMs in the absence of cloud radiative effects?

NASA Astrophysics Data System (ADS)

Popke, Dagmar; Bony, Sandrine; Mauritsen, Thorsten; Stevens, Bjorn

2015-04-01

Model simulations with state-of-the-art general circulation models reveal a strong disagreement concerning the simulated regional precipitation patterns and their changes with warming. The deviating precipitation response even persists when reducing the model experiment complexity to aquaplanet simulation with forced sea surface temperatures (Stevens and Bony, 2013). To assess feedbacks between clouds and radiation on precipitation responses we analyze data from 5 models performing the aquaplanet simulations of the Clouds On Off Klima Intercomparison Experiment (COOKIE), where the interaction of clouds and radiation is inhibited. Although cloud radiative effects are then disabled, the precipitation patterns among models are as diverse as with cloud radiative effects switched on. Disentangling differing model responses in such simplified experiments thus appears to be key to better understanding the simulated regional precipitation in more standard configurations. By analyzing the local moisture and moist static energy budgets in the COOKIE experiments we investigate likely causes for the disagreement among models. References Stevens, B. & S. Bony: What Are Climate Models Missing?, Science, 2013, 340, 1053-1054

Cirrus cloud retrieval from MSG/SEVIRI during day and night using artificial neural networks

NASA Astrophysics Data System (ADS)

Strandgren, Johan; Bugliaro, Luca

2017-04-01

By covering a large part of the Earth, cirrus clouds play an important role in climate as they reflect incoming solar radiation and absorb outgoing thermal radiation. Nevertheless, the cirrus clouds remain one of the largest uncertainties in atmospheric research and the understanding of the physical processes that govern their life cycle is still poorly understood, as is their representation in climate models. To monitor and better understand the properties and physical processes of cirrus clouds, it's essential that those tenuous clouds can be observed from geostationary spaceborne imagers like SEVIRI (Spinning Enhanced Visible and InfraRed Imager), that possess a high temporal resolution together with a large field of view and play an important role besides in-situ observations for the investigation of cirrus cloud processes. CiPS (Cirrus Properties from Seviri) is a new algorithm targeting thin cirrus clouds. CiPS is an artificial neural network trained with coincident SEVIRI and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) observations in order to retrieve a cirrus cloud mask along with the cloud top height (CTH), ice optical thickness (IOT) and ice water path (IWP) from SEVIRI. By utilizing only the thermal/IR channels of SEVIRI, CiPS can be used during day and night making it a powerful tool for the cirrus life cycle analysis. Despite the great challenge of detecting thin cirrus clouds and retrieving their properties from a geostationary imager using only the thermal/IR wavelengths, CiPS performs well. Among the cirrus clouds detected by CALIOP, CiPS detects 70 and 95 % of the clouds with an optical thickness of 0.1 and 1.0 respectively. Among the cirrus free pixels, CiPS classify 96 % correctly. For the CTH retrieval, CiPS has a mean absolute percentage error of 10 % or less with respect to CALIOP for cirrus clouds with a CTH greater than 8 km. For the IOT retrieval, CiPS has a mean absolute percentage error of 100 % or less with respect to CALIOP for cirrus clouds with an optical thickness down to 0.07. For such thin cirrus clouds an error of 100 % should be regarded as low from a geostationary imager like SEVIRI. The IWP retrieved by CiPS shows a similar performance, but has larger deviations for the thinner cirrus clouds.

A Radiative Analysis of Angular Signatures and Oblique Radiance Retrievals over the Polar Regions from the Multi-Angle Imaging Spectroradiometer

ERIC Educational Resources Information Center

Wilson, Michael Jason

2009-01-01

This dissertation studies clouds over the polar regions using the Multi-angle Imaging SpectroRadiometer (MISR) on-board EOS-Terra. Historically, low thin clouds have been problematic for satellite detection, because these clouds have similar brightness and temperature properties to the surface they overlay. However, the oblique angles of MISR…

Supporting reputation based trust management enhancing security layer for cloud service models

NASA Astrophysics Data System (ADS)

Karthiga, R.; Vanitha, M.; Sumaiya Thaseen, I.; Mangaiyarkarasi, R.

2017-11-01

In the existing system trust between cloud providers and consumers is inadequate to establish the service level agreement though the consumer’s response is good cause to assess the overall reliability of cloud services. Investigators recognized the significance of trust can be managed and security can be provided based on feedback collected from participant. In this work a face recognition system that helps to identify the user effectively. So we use an image comparison algorithm where the user face is captured during registration time and get stored in database. With that original image we compare it with the sample image that is already stored in database. If both the image get matched then the users are identified effectively. When the confidential data are subcontracted to the cloud, data holders will become worried about the confidentiality of their data in the cloud. Encrypting the data before subcontracting has been regarded as the important resources of keeping user data privacy beside the cloud server. So in order to keep the data secure we use an AES algorithm. Symmetric-key algorithms practice a shared key concept, keeping data secret requires keeping this key secret. So only the user with private key can decrypt data.

Improved Modeling Tools Development for High Penetration Solar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Washom, Byron; Meagher, Kevin

2014-12-11

One of the significant objectives of the High Penetration solar research is to help the DOE understand, anticipate, and minimize grid operation impacts as more solar resources are added to the electric power system. For Task 2.2, an effective, reliable approach to predicting solar energy availability for energy generation forecasts using the University of California, San Diego (UCSD) Sky Imager technology has been demonstrated. Granular cloud and ramp forecasts for the next 5 to 20 minutes over an area of 10 square miles were developed. Sky images taken every 30 seconds are processed to determine cloud locations and cloud motionmore » vectors yielding future cloud shadow locations respective to distributed generation or utility solar power plants in the area. The performance of the method depends on cloud characteristics. On days with more advective cloud conditions, the developed method outperforms persistence forecasts by up to 30% (based on mean absolute error). On days with dynamic conditions, the method performs worse than persistence. Sky Imagers hold promise for ramp forecasting and ramp mitigation in conjunction with inverter controls and energy storage. The pre-commercial Sky Imager solar forecasting algorithm was documented with licensing information and was a Sunshot website highlight.« less

3D change detection at street level using mobile laser scanning point clouds and terrestrial images

NASA Astrophysics Data System (ADS)

Qin, Rongjun; Gruen, Armin

2014-04-01

Automatic change detection and geo-database updating in the urban environment are difficult tasks. There has been much research on detecting changes with satellite and aerial images, but studies have rarely been performed at the street level, which is complex in its 3D geometry. Contemporary geo-databases include 3D street-level objects, which demand frequent data updating. Terrestrial images provides rich texture information for change detection, but the change detection with terrestrial images from different epochs sometimes faces problems with illumination changes, perspective distortions and unreliable 3D geometry caused by the lack of performance of automatic image matchers, while mobile laser scanning (MLS) data acquired from different epochs provides accurate 3D geometry for change detection, but is very expensive for periodical acquisition. This paper proposes a new method for change detection at street level by using combination of MLS point clouds and terrestrial images: the accurate but expensive MLS data acquired from an early epoch serves as the reference, and terrestrial images or photogrammetric images captured from an image-based mobile mapping system (MMS) at a later epoch are used to detect the geometrical changes between different epochs. The method will automatically mark the possible changes in each view, which provides a cost-efficient method for frequent data updating. The methodology is divided into several steps. In the first step, the point clouds are recorded by the MLS system and processed, with data cleaned and classified by semi-automatic means. In the second step, terrestrial images or mobile mapping images at a later epoch are taken and registered to the point cloud, and then point clouds are projected on each image by a weighted window based z-buffering method for view dependent 2D triangulation. In the next step, stereo pairs of the terrestrial images are rectified and re-projected between each other to check the geometrical consistency between point clouds and stereo images. Finally, an over-segmentation based graph cut optimization is carried out, taking into account the color, depth and class information to compute the changed area in the image space. The proposed method is invariant to light changes, robust to small co-registration errors between images and point clouds, and can be applied straightforwardly to 3D polyhedral models. This method can be used for 3D street data updating, city infrastructure management and damage monitoring in complex urban scenes.

Reconstructing spatial-temporal continuous MODIS land surface temperature using the DINEOF method

NASA Astrophysics Data System (ADS)

Zhou, Wang; Peng, Bin; Shi, Jiancheng

2017-10-01

Land surface temperature (LST) is one of the key states of the Earth surface system. Remote sensing has the capability to obtain high-frequency LST observations with global coverage. However, mainly due to cloud cover, there are always gaps in the remotely sensed LST product, which hampers the application of satellite-based LST in data-driven modeling of surface energy and water exchange processes. We explored the suitability of the data interpolating empirical orthogonal functions (DINEOF) method in moderate resolution imaging spectroradiometer LST reconstruction around Ali on the Tibetan Plateau. To validate the reconstruction accuracy, synthetic clouds during both daytime and nighttime are created. With DINEOF reconstruction, the root mean square error and bias under synthetic clouds in daytime are 4.57 and -0.0472 K, respectively, and during the nighttime are 2.30 and 0.0045 K, respectively. The DINEOF method can well recover the spatial pattern of LST. Time-series analysis of LST before and after DINEOF reconstruction from 2002 to 2016 shows that the annual and interannual variabilities of LST can be well reconstructed by the DINEOF method.

Titan Moving Mid-Latitude Clouds

NASA Image and Video Library

2011-03-17

This image shows clouds in the mid-southern latitudes of Saturn largest moon, Titan, one of a series of images captured by NASA Cassini spacecraft a few months after fall began in the southern hemisphere.

Cloud Optimized Image Format and Compression

NASA Astrophysics Data System (ADS)

Becker, P.; Plesea, L.; Maurer, T.

2015-04-01

Cloud based image storage and processing requires revaluation of formats and processing methods. For the true value of the massive volumes of earth observation data to be realized, the image data needs to be accessible from the cloud. Traditional file formats such as TIF and NITF were developed in the hay day of the desktop and assumed fast low latency file access. Other formats such as JPEG2000 provide for streaming protocols for pixel data, but still require a server to have file access. These concepts no longer truly hold in cloud based elastic storage and computation environments. This paper will provide details of a newly evolving image storage format (MRF) and compression that is optimized for cloud environments. Although the cost of storage continues to fall for large data volumes, there is still significant value in compression. For imagery data to be used in analysis and exploit the extended dynamic range of the new sensors, lossless or controlled lossy compression is of high value. Compression decreases the data volumes stored and reduces the data transferred, but the reduced data size must be balanced with the CPU required to decompress. The paper also outlines a new compression algorithm (LERC) for imagery and elevation data that optimizes this balance. Advantages of the compression include its simple to implement algorithm that enables it to be efficiently accessed using JavaScript. Combing this new cloud based image storage format and compression will help resolve some of the challenges of big image data on the internet.

Accuracy assessment of building point clouds automatically generated from iphone images

NASA Astrophysics Data System (ADS)

Sirmacek, B.; Lindenbergh, R.

2014-06-01

Low-cost sensor generated 3D models can be useful for quick 3D urban model updating, yet the quality of the models is questionable. In this article, we evaluate the reliability of an automatic point cloud generation method using multi-view iPhone images or an iPhone video file as an input. We register such automatically generated point cloud on a TLS point cloud of the same object to discuss accuracy, advantages and limitations of the iPhone generated point clouds. For the chosen example showcase, we have classified 1.23% of the iPhone point cloud points as outliers, and calculated the mean of the point to point distances to the TLS point cloud as 0.11 m. Since a TLS point cloud might also include measurement errors and noise, we computed local noise values for the point clouds from both sources. Mean (μ) and standard deviation (σ) of roughness histograms are calculated as (μ1 = 0.44 m., σ1 = 0.071 m.) and (μ2 = 0.025 m., σ2 = 0.037 m.) for the iPhone and TLS point clouds respectively. Our experimental results indicate possible usage of the proposed automatic 3D model generation framework for 3D urban map updating, fusion and detail enhancing, quick and real-time change detection purposes. However, further insights should be obtained first on the circumstances that are needed to guarantee a successful point cloud generation from smartphone images.

Overview of CERES Cloud Properties Derived From VIRS AND MODIS DATA

NASA Technical Reports Server (NTRS)

Minis, Patrick; Geier, Erika; Wielicki, Bruce A.; Sun-Mack, Sunny; Chen, Yan; Trepte, Qing Z.; Dong, Xiquan; Doelling, David R.; Ayers, J. Kirk; Khaiyer, Mandana M.

2006-01-01

Simultaneous measurement of radiation and cloud fields on a global basis is recognized as a key component in understanding and modeling the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project (Wielicki et al., 1998) began addressing this issue in 1998 with its first broadband shortwave and longwave scanner on the Tropical Rainfall Measuring Mission (TRMM). This was followed by the launch of two CERES scanners each on Terra and Aqua during late 1999 and early 2002, respectively. When combined, these satellites should provide the most comprehensive global characterization of clouds and radiation to date. Unfortunately, the TRMM scanner failed during late 1998. The Terra and Aqua scanners continue to operate, however, providing measurements at a minimum of 4 local times each day. CERES was designed to scan in tandem with high resolution imagers so that the cloud conditions could be evaluated for every CERES measurement. The cloud properties are essential for converting CERES radiances shortwave albedo and longwave fluxes needed to define the radiation budget (ERB). They are also needed to unravel the impact of clouds on the ERB. The 5-channel, 2-km Visible Infrared Scanner (VIRS) on the TRMM and the 36-channel 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua are analyzed to define the cloud properties for each CERES footprint. To minimize inter-satellite differences and aid the development of useful climate-scale measurements, it was necessary to ensure that each satellite imager is calibrated in a fashion consistent with its counterpart on the other CERES satellites (Minnis et al., 2006) and that the algorithms are as similar as possible for all of the imagers. Thus, a set of cloud detection and retrieval algorithms were developed that could be applied to all three imagers utilizing as few channels as possible while producing stable and accurate cloud properties. This paper discusses the algorithms and results of applying those techniques to more than 5 years of Terra MODIS, 3 years of Aqua MODIS, and 4 years of TRMM VIRS data.

Observations of Aerosol-Cloud Interactions with Varying Vertical Separation between Biomass-Burning Aerosols and Stratocumulus Clouds over the South East Atlantic

NASA Astrophysics Data System (ADS)

Gupta, S.; McFarquhar, G. M.; Poellot, M.; O'Brien, J.; Delene, D. J.; Thornhill, K. L., II

2017-12-01

The ObseRvations of Aerosols above Clouds and their intEractionS (ORACLES) 2016 project provided in-situ measurements and remotely sensed retrievals of aerosol and cloud properties over the South East Atlantic during September, 2016 with a second deployment scheduled for August, 2017. Biomass burning aerosol from Southern Africa is advected toward the South East Atlantic at elevated altitudes and overlies the ubiquitous stratocumulus cloud deck over the ocean. The aerosols subside farther from the coast so that the vertical displacement between the clouds and aerosols varies, and whose effect on aerosol-cloud interaction is poorly known. A NASA P-3 aircraft was equipped with a Cloud Droplet Probe CDP sizing particles between 2 and 50μm, a Cloud and Aerosol Spectrometer CAS sizing between 0.51 and 50 μm and a 2D-stereo probe 2DS, nominally sizing between 10 and 1280 μm a Cloud Imaging Probe CIP, from 25 to 1600μm, and a High Volume Precipitation Sampler HVPS-3, from 150μm to 1.92cm for measuring number distribution functions (n(D)) along with a King probe for measuring liquid water content, LWC. A Passive Cavity Aerosol Spectrometer Probe PCASP measured aerosol particles between 0.1 to 3μm. Cloud legs from three research flights are classified into different regimes based on the aerosol concentration measured in the accumulation mode by the PCASP (Na) and its location above clouds. These legs include vertical transects through clouds and sawtooths (ramped legs starting above or below the cloud layer, completing a vertical transect through the cloud and repeating this pattern for several legs). The regimes; clean, mixing and separated, correspond to conditions with Na less than 100 cm-3 above cloud top, Na greater than 100 cm-3 within 100 m above cloud top and Na greater than 100 cm-3 separated from the cloud top by more than 100 m. During the mixing regime, measurements from CAS and 2DS show that droplet concentrations and cloud optical depths increased and effective radii decreased, relative to other regimes. Drizzle suppression with lower probability of occurrence of drizzle drops (diameter greater than 50 um) and entrainment of dry air with decreased droplet concentrations near cloud tops was also observed. Similar LWC was observed across regimes with similar vertical velocities during the cloud legs.

Estimation of Cirrus and Stratus Cloud Heights Using Landsat Imagery

NASA Technical Reports Server (NTRS)

Inomata, Yasushi; Feind, R. E.; Welch, R. M.

1996-01-01

A new method based upon high-spatial-resolution imagery is presented that matches cloud and shadow regions to estimate cirrus and stratus cloud heights. The distance between the cloud and the matching shadow pattern is accomplished using the 2D cross-correlation function from which the cloud height is derived. The distance between the matching cloud-shadow patterns is verified manually. The derived heights also are validated through comparison with a temperature-based retrieval of cloud height. It is also demonstrated that an estimate of cloud thickness can be retrieved if both the sunside and anti-sunside of the cloud-shadow pair are apparent. The technique requires some intepretation to determine the cloud height level retrieved (i.e., the top, base, or mid-level). It is concluded that the method is accurate to within several pixels, equivalent to cloud height variations of about +/- 250 m. The results show that precise placement of the templates is unnecessary, so that the development of a semi-automated procedure is possible. Cloud templates of about 64 pixels on a side or larger produce consistent results. The procedure was repeated for imagery degraded to simulate lower spatial resolutions. The results suggest that spatial resolution of 150-200 m or better is necessary in order to obtain stable cloud height retrievals.

Earth Observations taken by Expedition 34 crewmember

NASA Image and Video Library

2013-01-04

ISS034-E-016601 (4 Jan. 2013) --- On Jan. 4 a large presence of stratocumulus clouds was the central focus of camera lenses which remained aimed at the clouds as the Expedition 34 crew members aboard the International Space Station flew above the northwestern Pacific Ocean about 460 miles east of northern Honshu, Japan. This is a descending pass with a panoramic view looking southeast in late afternoon light with the terminator (upper left). The cloud pattern is typical for this part of the world. The low clouds carry cold air over a warmer sea with no discernable storm pattern.

Saturn Methane Image

NASA Image and Video Library

2004-03-05

NASA's Cassini narrow angle camera took this image of Saturn on Feb. 16, 2004, from a distance of 66.1 million kilometers (41.1 million miles) in a special filter which reveals clouds and haze high in the atmosphere. The image scale is 397 kilometers (247 miles) per pixel. The MT2 spectral filter samples a near-infrared region of the electromagnetic spectrum where methane gas absorbs light at a wavelength of 727 nanometers. In the image, methane gas is uniformly mixed with hydrogen, the main gas in Saturn's atmosphere. Dark locales are places of strong methane absorption, relatively free of high clouds; the bright areas are places with high, thick clouds which shield the methane below. Image details reveal a high, thick equatorial cloud and a relatively deep or thin haze encircling the pole, as well as several distinct latitude bands with different cloud height attributes. It also shows a high atmospheric disturbance, just south of the equator, which has persisted throughout the 1990s in images returned by NASA's Hubble Space Telescope. Four of Saturn's moons are visible (clockwise from above right): Enceladus (499 kilometers, or 310 miles across); Mimas (396 kilometers, or 245 miles across); Tethys (1,060 kilometers, or 659 miles across); and Rhea (1,528 kilometers, or 949 miles across). The imaging team enhanced the brightness of Mimas and Enceladus by a factor of three. http://photojournal.jpl.nasa.gov/catalog/PIA05381

Automatic registration of Iphone images to LASER point clouds of the urban structures using shape features

NASA Astrophysics Data System (ADS)

Sirmacek, B.; Lindenbergh, R. C.; Menenti, M.

2013-10-01

Fusion of 3D airborne laser (LIDAR) data and terrestrial optical imagery can be applied in 3D urban modeling and model up-dating. The most challenging aspect of the fusion procedure is registering the terrestrial optical images on the LIDAR point clouds. In this article, we propose an approach for registering these two different data from different sensor sources. As we use iPhone camera images which are taken in front of the interested urban structure by the application user and the high resolution LIDAR point clouds of the acquired by an airborne laser sensor. After finding the photo capturing position and orientation from the iPhone photograph metafile, we automatically select the area of interest in the point cloud and transform it into a range image which has only grayscale intensity levels according to the distance from the image acquisition position. We benefit from local features for registering the iPhone image to the generated range image. In this article, we have applied the registration process based on local feature extraction and graph matching. Finally, the registration result is used for facade texture mapping on the 3D building surface mesh which is generated from the LIDAR point cloud. Our experimental results indicate possible usage of the proposed algorithm framework for 3D urban map updating and enhancing purposes.

Pattern of downstream eddies in stratocumulus clouds over Pacific Ocean

NASA Image and Video Library

1973-08-01

SL3-121-2371 (July-September 1973) --- A pattern of downstream eddies in the stratocumulus clouds over the Pacific Ocean west of Baja California, as photographed by the crewmen of the second Skylab manned mission (Skylab 3) from the space station cluster in Earth orbit. The clouds, produced by the cold California current running to the south and southwest, are prevented from rising by warm air above them. Photo credit: NASA

Infrared cloud imaging in support of Earth-space optical communication.

PubMed

Nugent, Paul W; Shaw, Joseph A; Piazzolla, Sabino

2009-05-11

The increasing need for high data return from near-Earth and deep-space missions is driving a demand for the establishment of Earth-space optical communication links. These links will require a nearly obstruction-free path to the communication platform, so there is a need to measure spatial and temporal statistics of clouds at potential ground-station sites. A technique is described that uses a ground-based thermal infrared imager to provide continuous day-night cloud detection and classification according to the cloud optical depth and potential communication channel attenuation. The benefit of retrieving cloud optical depth and corresponding attenuation is illustrated through measurements that identify cloudy times when optical communication may still be possible through thin clouds.

Space Shuttle Video Images: An Example of Warm Cloud Lightning

NASA Technical Reports Server (NTRS)

Vaughan, Otha H., Jr.; Boeck, William L.

1998-01-01

Warm cloud lightning has been reported in several tropical locations. We have been using the intensified monochrome TV cameras at night during a number of shuttle flights to observe large active thunderstorms and their associated lightning. During a nighttime orbital pass of the STS-70 mission on 17 July 1995 at 07:57:42 GMT, the controllers obtained video imagery of a small cloud that was producing lightning. Data from a GOES infrared image establishes that the cloud top had a temperature of about 271 degrees Kelvin ( -2 degrees Celsius). Since this cloud was electrified to the extent that a lightning discharge did occur, it may be another case of lightning in a cloud that presents little if any evidence of frozen or melting precipitation.

View of clouds over Indian Ocean taken by Astronaut John Glenn during MA-6

NASA Technical Reports Server (NTRS)

1962-01-01

A view of clouds over the Indian Ocean as photographed by Astronaut John H. Glenn Jr. aboard the 'Friendship 7' spacecraft on February 20, 1962. The cloud panorama illustrates the visibility of different cloud types and weather patterns. Shadows produced by the rising Sun aid in the determination of relative cloud heights.

Development of Multi-Sensor Global Cloud and Radiance Composites for DSCOVR EPIC Imager with Subpixel Definition

NASA Astrophysics Data System (ADS)

Khlopenkov, K. V.; Duda, D. P.; Thieman, M. M.; Sun-Mack, S.; Su, W.; Minnis, P.; Bedka, K. M.

2017-12-01

The Deep Space Climate Observatory (DSCOVR) is designed to study the daytime Earth radiation budget by means of onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). EPIC imager observes in several shortwave bands (317-780 nm), while NISTAR measures the top-of-atmosphere (TOA) whole-disk radiance in shortwave and total broadband windows. Calculation of albedo and outgoing longwave flux requires a high-resolution scene identification such as the radiance observations and cloud property retrievals from low earth orbit and geostationary satellite imagers. These properties have to be co-located with EPIC imager pixels to provide scene identification and to select anisotropic directional models, which are then used to adjust the NISTAR-measured radiance and subsequently obtain the global daytime shortwave and longwave fluxes. This work presents an algorithm for optimal merging of selected radiances and cloud properties derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. The highest quality observation is selected by means of an aggregated rating which incorporates several factors such as the nearest time relative to EPIC observation, lowest viewing zenith angle, and others. This process provides a smoother transition and avoids abrupt changes in the merged composite data. Higher spatial accuracy in the composite product is achieved by using the inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling. The composite data are subsequently remapped into the EPIC-view domain by convolving composite pixels with the EPIC point spread function (PSF) defined with a half-pixel accuracy. Within every EPIC footprint, the PSF-weighted average radiances and cloud properties are computed for each cloud phase and then stored within five data subsets (clear-sky, water cloud, ice cloud, total cloud, and no retrieval). Overall, the composite product has been generated for every EPIC observation from June 2015 to December 2016, typically 300-500 composites per month, which makes it useful for many climate applications.

Tropical Depression 6 Florence in the Atlantic

NASA Image and Video Library

2006-09-03

This infrared image shows Tropical Depression 6 Florence in the Atlantic, from the Atmospheric Infrared Sounder AIRS on NASA Aqua satellite in September, 2006. Because infrared radiation does not penetrate through clouds, AIRS infrared images show either the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures (in purple) are associated with high, cold cloud tops that make up the top of the storm. In cloud-free areas the AIRS instrument will receive the infrared radiation from the surface of the Earth, resulting in the warmest temperatures (orange/red). http://photojournal.jpl.nasa.gov/catalog/PIA00512

ARC-1979-AC79-7105

NASA Image and Video Library

1979-07-06

Range : 3.2 million km This image returned by Voyager 2 shows one of the long dark clouds observed in the North Equatorial Belt of Jupiter. A high, white cloud is seen moving over the darker cloud, providing an indication of the structure of the cloud layers. Thin white clouds are also seen within the dark cloud. At right, blue areas, free of high clouds, are seen.

Space Radar Image of Maui, Hawaii

NASA Image and Video Library

1999-04-15

This spaceborne radar image shows the Valley Island of Maui, Hawaii. The cloud-penetrating capabilities of radar provide a rare view of many parts of the island, since the higher elevations are frequently shrouded in clouds.

Observations of Three-Dimensional Radiative Effects that Influence Satellite Retrievals of Cloud Properties

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander; Lau, William K. M. (Technical Monitor)

2001-01-01

This paper examines three-dimensional (3D) radiative effects, which arise from horizontal radiative interactions between areas that have different cloud properties. Earlier studies have argued that these effects can cause significant uncertainties in current satellite retrievals of cloud properties, because the retrievals rely on one-dimensional (1D) theory and do not consider the effects of horizontal changes in cloud properties. This study addresses two questions: which retrieved cloud properties are influenced by 3D radiative effects, and where 3D effects tend to occur? The influence of 3D effects is detected from the wayside illumination and shadowing make clouds appear asymmetric: Areas appear brighter if the cloud top surface is tilted toward, rather than away from, the Sun. The analysis of 30 images by the Moderate Resolution Imaging Spectroradiometer (MODIS) reveals that retrievals of cloud optical thickness and cloud water content are most influenced by 3D effects, whereas retrievals of cloud particle size are much less affected. The results also indicate that while 3D effects are strongest at cloud edges, cloud top variability in cloud interiors, even in overcast regions, also produces considerable 3D effects. Finally, significant 3D effects are found in a wide variety of situations, ranging from thin clouds to thick ones and from low clouds to high ones.

Diurnal and Seasonal Cloud Base Patterns Highlight Small-Mountain Tropical Cloud Forest Vulnerability

NASA Astrophysics Data System (ADS)

Van Beusekom, A.; Gonzalez, G.; Scholl, M. A.

2016-12-01

The degree to which cloud immersion sustains tropical montane cloud forests (TMCFs) during rainless periods and the amount these clouds are affected by urban areas is not well understood, as cloud base is rarely quantified near mountains. We found that a healthy small-mountain TMCF in Puerto Rico had lowest cloud base during the mid-summer dry season. In addition, we observed that cloud bases were lower than the mountaintops as often in the winter dry season as in the wet seasons, based on 2.5 years of direct and 16 years of indirect observations. The low clouds during dry season appear to be explained by proximity to the oceanic cloud system where lower clouds are seasonally invariant in altitude and cover; along with orographic lifting and trade-wind control over cloud formation. These results suggest that climate change impacts on small-mountain TMCFs may not be limited to the dry season; changes in regional-scale patterns that cause drought periods during the wet seasons will likely have higher cloud base, and thus may threaten cloud water support to sensitive mountain ecosystems. Strong El Niño's can cause drought in Puerto Rico; we will report results from the summer of 2015 that examined El Niño effects on cloud base altitudes. Looking at regionally collected airport cloud data, we see indicators that diurnal urban effects may already be raising the low cloud bases.

A network approach to the geometric structure of shallow cloud fields

NASA Astrophysics Data System (ADS)

Glassmeier, F.; Feingold, G.

2017-12-01

The representation of shallow clouds and their radiative impact is one of the largest challenges for global climate models. While the bulk properties of cloud fields, including effects of organization, are a very active area of research, the potential of the geometric arrangement of cloud fields for the development of new parameterizations has hardly been explored. Self-organized patterns are particularly evident in the cellular structure of Stratocumulus (Sc) clouds so readily visible in satellite imagery. Inspired by similar patterns in biology and physics, we approach pattern formation in Sc fields from the perspective of natural cellular networks. Our network analysis is based on large-eddy simulations of open- and closed-cell Sc cases. We find the network structure to be neither random nor characteristic to natural convection. It is independent of macroscopic cloud fields properties like the Sc regime (open vs closed) and its typical length scale (boundary layer height). The latter is a consequence of entropy maximization (Lewis's Law with parameter 0.16). The cellular pattern is on average hexagonal, where non-6 sided cells occur according to a neighbor-number distribution variance of about 2. Reflecting the continuously renewing dynamics of Sc fields, large (many-sided) cells tend to neighbor small (few-sided) cells (Aboav-Weaire Law with parameter 0.9). These macroscopic network properties emerge independent of the Sc regime because the different processes governing the evolution of closed as compared to open cells correspond to topologically equivalent network dynamics. By developing a heuristic model, we show that open and closed cell dynamics can both be mimicked by versions of cell division and cell disappearance and are biased towards the expansion of smaller cells. This model offers for the first time a fundamental and universal explanation for the geometric pattern of Sc clouds. It may contribute to the development of advanced Sc parameterizations. As an outlook, we discuss how a similar network approach can be applied to describe and quantify the geometric structure of shallow cumulus cloud fields.

Assessment of the first indirect radiative effect of ammonium-sulfate-nitrate aerosols in East Asia

NASA Astrophysics Data System (ADS)

Han, Xiao; Zhang, Meigen; Skorokhod, Andrei

2017-11-01

A physically based cloud nucleation parameterization was introduced into an optical properties/radiative transfer module incorporated with the off-line air quality modeling system Regional Atmospheric Modeling System (RAMS)-Models-3 Community Multi Scale Air Quality (CMAQ) to investigate the distribution features of the first indirect radiative effects of sulfate, nitrate, and ammonium-sulfate-nitrate (ASN) over East Asia for the years of 2005, 2010, and 2013. The relationship between aerosol particles and cloud droplet number concentration could be properly described by this parameterization because the simulated cloud fraction and cloud liquid water path were generally reliable compared with Moderate Resolution Imaging Spectroradiometer (MODIS) retrieved data. Simulation results showed that the strong effect of indirect forcing was mainly concentrated in Southeast China, the East China Sea, the Yellow Sea, and the Sea of Japan. The highest indirect radiative forcing of ASN reached -3.47 W m-2 over Southeast China and was obviously larger than the global mean of the indirect forcing of all anthropogenic aerosols. In addition, sulfate provided about half of the contribution to the ASN indirect forcing effect. However, the effect caused by nitrate was weak because the mass burden of nitrate was very low during summer, whereas the cloud fraction was the highest. The analysis indicated that even though the interannual variation of indirect forcing magnitude generally followed the trend of aerosol mass burden from 2005 to 2013, the cloud fraction was an important factor that determined the distribution pattern of indirect forcing. The heaviest aerosol loading in North China did not cause a strong radiative effect because of the low cloud fraction over this region.

Identification Code of Interstellar Cloud within IRAF

NASA Astrophysics Data System (ADS)

Lee, Youngung; Jung, Jae Hoon; Kim, Hyun-Goo

1997-12-01

We present a code which identifies individual clouds in crowded region using IMFORT interface within Image Reduction and Analysis Facility(IRAF). We define a cloud as an object composed of all pixels in longitude, latitude, and velocity that are simply connected and that lie above some threshold temperature. The code searches the whole pixels of the data cube in efficient way to isolate individual clouds. Along with identification of clouds it is designed to estimate their mean values of longitudes, latitudes, and velocities. In addition, a function of generating individual images(or cube data) of identified clouds is added up. We also present identified individual clouds using a 12CO survey data cube of Galactic Anticenter Region(Lee et al. 1997) as a test example. We used a threshold temperature of 5 sigma rms noise level of the data. With a higher threshold temperature, we isolated subclouds of a huge cloud identified originally. As the most important parameter to identify clouds is the threshold value, its effect to the size and velocity dispersion is discussed rigorously.

The registration of non-cooperative moving targets laser point cloud in different view point

NASA Astrophysics Data System (ADS)

Wang, Shuai; Sun, Huayan; Guo, Huichao

2018-01-01

Non-cooperative moving target multi-view cloud registration is the key technology of 3D reconstruction of laser threedimension imaging. The main problem is that the density changes greatly and noise exists under different acquisition conditions of point cloud. In this paper, firstly, the feature descriptor is used to find the most similar point cloud, and then based on the registration algorithm of region segmentation, the geometric structure of the point is extracted by the geometric similarity between point and point, The point cloud is divided into regions based on spectral clustering, feature descriptors are created for each region, searching to find the most similar regions in the most similar point of view cloud, and then aligning the pair of point clouds by aligning their minimum bounding boxes. Repeat the above steps again until registration of all point clouds is completed. Experiments show that this method is insensitive to the density of point clouds and performs well on the noise of laser three-dimension imaging.

Quantifying Structural and Compositional Changes in Forest Cover in NW Yunnan, China

NASA Astrophysics Data System (ADS)

Hakkenberg, C.

2012-12-01

NW Yunnan, China is a region renowned for high levels of biodiversity, endemism and genetically distinct refugial plant populations. It is also a focal area for China's national reforestation efforts like the Natural Forest Protection Program (NFPP), intended to control erosion in the Upper Yangtze watershed. As part of a larger project to investigate the role of reforestation programs in facilitating the emergence of increasingly species-rich forest communities on a previously degraded and depauperate land mosaic in montane SW China, this study uses a series of Landsat TM images to quantify the spatial pattern and rate of structural and compositional change in forests recovering from medium to large-scale disturbances in the area over the past 25 years. Beyond the fundamental need to assess the outcomes of one of the world's largest reforestation programs, this research offers approaches to confronting two critical methodological issues: (1) techniques for characterizing subtle changes in the nature of vegetation cover, and (2) reducing change detection uncertainty due to persistent cloud cover and shadow. To address difficulties in accurately assessing the structure and composition of vegetative regrowth, a biophysical model was parameterized with over 300 ground-truthed canopy cover assessment points to determine pattern and rate of long-term vegetation changes. To combat pervasive shadow and cloud cover, an interactive generalized additive model (GAM) model based on topographic and spatial predictors was used to overcome some of the constraints of satellite image analysis in Himalayan regions characterized by extreme topography and extensive cloud cover during the summer monsoon. The change detection is assessed for accuracy using ground-truthed observations in a variety of forest cover types and topographic positions. Results indicate effectiveness in reducing the areal extent of unclassified regions and increasing total change detection accuracy. In addition to quantifying forest cover change in this section of NW Yunnan, the analysis attempts to qualify that change - distinguishing among distinct disturbance histories and post-recovery successional pathways.

Cloud-based image sharing network for collaborative imaging diagnosis and consultation

NASA Astrophysics Data System (ADS)

Yang, Yuanyuan; Gu, Yiping; Wang, Mingqing; Sun, Jianyong; Li, Ming; Zhang, Weiqiang; Zhang, Jianguo

2018-03-01

In this presentation, we presented a new approach to design cloud-based image sharing network for collaborative imaging diagnosis and consultation through Internet, which can enable radiologists, specialists and physicians locating in different sites collaboratively and interactively to do imaging diagnosis or consultation for difficult or emergency cases. The designed network combined a regional RIS, grid-based image distribution management, an integrated video conferencing system and multi-platform interactive image display devices together with secured messaging and data communication. There are three kinds of components in the network: edge server, grid-based imaging documents registry and repository, and multi-platform display devices. This network has been deployed in a public cloud platform of Alibaba through Internet since March 2017 and used for small lung nodule or early staging lung cancer diagnosis services between Radiology departments of Huadong hospital in Shanghai and the First Hospital of Jiaxing in Zhejiang Province.

Fast Monte Carlo-assisted simulation of cloudy Earth backgrounds

NASA Astrophysics Data System (ADS)

Adler-Golden, Steven; Richtsmeier, Steven C.; Berk, Alexander; Duff, James W.

2012-11-01

A calculation method has been developed for rapidly synthesizing radiometrically accurate ultraviolet through longwavelengthinfrared spectral imagery of the Earth for arbitrary locations and cloud fields. The method combines cloudfree surface reflectance imagery with cloud radiance images calculated from a first-principles 3-D radiation transport model. The MCScene Monte Carlo code [1-4] is used to build a cloud image library; a data fusion method is incorporated to speed convergence. The surface and cloud images are combined with an upper atmospheric description with the aid of solar and thermal radiation transport equations that account for atmospheric inhomogeneity. The method enables a wide variety of sensor and sun locations, cloud fields, and surfaces to be combined on-the-fly, and provides hyperspectral wavelength resolution with minimal computational effort. The simulations agree very well with much more time-consuming direct Monte Carlo calculations of the same scene.

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

NASA Astrophysics Data System (ADS)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-04-01

This paper presents an investigation of the expected uncertainties of a single-channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud-temperature-threshold-based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC Sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single-channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single-channel COT retrieval is feasible for EPIC. For ice clouds, single-channel retrieval errors are minimal (< 2 %) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10 %, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

Automated cloud classification with a fuzzy logic expert system

NASA Technical Reports Server (NTRS)

Tovinkere, Vasanth; Baum, Bryan A.

1993-01-01

An unresolved problem in current cloud retrieval algorithms concerns the analysis of scenes containing overlapping cloud layers. Cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget. Most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. One promising method uses fuzzy logic to determine whether mixed cloud and/or surface types exist within a group of pixels, such as cirrus, land, and water, or cirrus and stratus. When two or more class types are present, fuzzy logic uses membership values to assign the group of pixels partially to the different class types. The strength of fuzzy logic lies in its ability to work with patterns that may include more than one class, facilitating greater information extraction from satellite radiometric data. The development of the fuzzy logic rule-based expert system involves training the fuzzy classifier with spectral and textural features calculated from accurately labeled 32x32 regions of Advanced Very High Resolution Radiometer (AVHRR) 1.1-km data. The spectral data consists of AVHRR channels 1 (0.55-0.68 mu m), 2 (0.725-1.1 mu m), 3 (3.55-3.93 mu m), 4 (10.5-11.5 mu m), and 5 (11.5-12.5 mu m), which include visible, near-infrared, and infrared window regions. The textural features are based on the gray level difference vector (GLDV) method. A sophisticated new interactive visual image Classification System (IVICS) is used to label samples chosen from scenes collected during the FIRE IFO II. The training samples are chosen from predefined classes, chosen to be ocean, land, unbroken stratiform, broken stratiform, and cirrus. The November 28, 1991 NOAA overpasses contain complex multilevel cloud situations ideal for training and validating the fuzzy logic expert system.

Evaluating the spatio-temporal performance of sky-imager-based solar irradiance analysis and forecasts

NASA Astrophysics Data System (ADS)

Schmidt, Thomas; Kalisch, John; Lorenz, Elke; Heinemann, Detlev

2016-03-01

Clouds are the dominant source of small-scale variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the worldwide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a very short term global horizontal irradiance (GHI) forecast experiment based on hemispheric sky images. A 2-month data set with images from one sky imager and high-resolution GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series into different cloud scenarios. Overall, the sky-imager-based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depends strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1-2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability, which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

Discrete cloud structure on Neptune

NASA Technical Reports Server (NTRS)

Hammel, H. B.

1989-01-01

Recent CCD imaging data for the discrete cloud structure of Neptune shows that while cloud features at CH4-band wavelengths are manifest in the southern hemisphere, they have not been encountered in the northern hemisphere since 1986. A literature search has shown the reflected CH4-band light from the planet to have come from a single discrete feature at least twice in the last 10 years. Disk-integrated photometry derived from the imaging has demonstrated that a bright cloud feature was responsible for the observed 8900 A diurnal variation in 1986 and 1987.

Effects of ice crystal surface roughness and air bubble inclusions on cirrus cloud radiative properties from remote sensing perspective

NASA Astrophysics Data System (ADS)

Tang, Guanglin; Panetta, R. Lee; Yang, Ping; Kattawar, George W.; Zhai, Peng-Wang

2017-07-01

We study the combined effects of surface roughness and inhomogeneity on the optical scattering properties of ice crystals and explore the consequent implications to remote sensing of cirrus cloud properties. Specifically, surface roughness and inhomogeneity are added to the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 (MC6) cirrus cloud particle habit model. Light scattering properties of the new habit model are simulated using a modified version of the Improved Geometric Optics Method (IGOM). Both inhomogeneity and surface roughness affect the single scattering properties significantly. In visible bands, inhomogeneity and surface roughness both tend to smooth the phase function and eliminate halos and the backscattering peak. The asymmetry parameter varies with the degree of surface roughness following a U shape - decreases and then increases - with a minimum at around 0.15, whereas it decreases monotonically with the air bubble volume fraction. Air bubble inclusions significantly increase phase matrix element -P12 for scattering angles between 20°-120°, whereas surface roughness has a much weaker effect, increasing -P12 slightly from 60°-120°. Radiative transfer simulations and cirrus cloud property retrievals are conducted by including both the factors. In terms of surface roughness and air bubble volume fraction, retrievals of cirrus cloud optical thickness or the asymmetry parameter using solar bands show similar patterns of variation. Polarimetric simulations using the MC6 cirrus cloud particle habit model are shown to be more consistent with observations when both surface roughness and inhomogeneity are simultaneously considered.

Quantifying the radiative and microphysical impacts of fire aerosols on cloud dynamics in the tropics using temporally offset satellite observations

NASA Astrophysics Data System (ADS)

Tosca, M. G.; Diner, D. J.; Garay, M. J.; Kalashnikova, O.

2013-12-01

Anthropogenic fires in Southeast Asia and Central America emit smoke that affects cloud dynamics, meteorology, and climate. We measured the cloud response to direct and indirect forcing from biomass burning aerosols using aerosol retrievals from the Multi-angle Imaging SpectroRadiometer (MISR) and non-synchronous cloud retrievals from the MODerate resolution Imaging Spectroradiometer (MODIS) from collocated morning and afternoon overpasses. Level 2 data from thirty-one individual scenes acquired between 2006 and 2010 were used to quantify changes in cloud fraction, cloud droplet size, cloud optical depth and cloud top temperature from morning (10:30am local time) to afternoon (1:30pm local time) in the presence of varying aerosol burdens. We accounted for large-scale meteorological differences between scenes by normalizing observed changes to the mean difference per individual scene. Elevated AODs reduced cloud fraction and cloud droplet size and increased cloud optical depths in both Southeast Asia and Central America. In mostly cloudy regions, aerosols significantly reduced cloud fraction and cloud droplet sizes, but in clear skies, cloud fraction, cloud optical thickness and cloud droplet sizes increased. In clouds with vertical development, aerosols reduced cloud fraction via semi-direct effects but spurred cloud growth via indirect effects. These results imply a positive feedback loop between anthropogenic burning and cloudiness in both Central America and Southeast Asia, and are consistent with previous studies linking smoke aerosols to both cloud reduction and convective invigoration.

A Change in the Weather

NASA Technical Reports Server (NTRS)

2007-01-01

These two Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) images were acquired over the northern plains of Mars near one of the possible landing sites for NASA's Phoenix mission, set to launch in August 2007. The lower right image was acquired first, on Nov. 29, 2006, at 0720 UTC (2:20 a.m. EST), while the upper left image was acquired about one month later on Dec. 26, 2006, at 0030 UTC (or Dec. 25, 2006, at 7:30 p.m. EST). The CRISM data were taken in 544 colors covering the wavelength range from 0.36-3.92 micrometers, and show features as small as about 20 meters (66 feet) across. The images shown above are red-green-blue color composites using wavelengths 0.71, 0.6, and 0.53 micrometers, respectively (or infrared, red, and green light), and are overlain on a mosaic of Mars Odyssey Thermal Emission Imaging System (THEMIS) visible data. Each image covers a region about 11 kilometers (6.6 miles) wide at its narrowest, and they overlap near 71.0 degrees north latitude, 252.8 degrees east longitude

The Earth equivalent to the season and latitude of this site is late summer in northern Canada, above the Arctic Circle. At that season and latitude, Martian weather conditions are transitioning from summer with generally clear skies, occasional weather fronts, and infrequent dust storms, to an autumn with pervasive, thick water-ice clouds.

The striking difference in the appearance of the images is caused by the seasonal development of water-ice clouds. The earlier (lower right) image is cloud-free, and surface features can clearly be seen - like the small crater in the upper left. However, the clouds and haze in the later (upper left) image make it hard to see the surface. There are variations in the thickness and spacing of the clouds, just like clouds on Earth. On other days when nearby sites were imaged, the cloud cover varied day-to-day, but as the seasons change the trend is more and thicker clouds.

With the onset of autumn the clouds will gradually cover the area and, just as with autumn on Earth, the Martian day is getting shorter at these high northern latitudes. In a few more months this area will settle into winter darkness and be covered in a layer of frost and carbon dioxide snow.

CRISM's mission: Find the spectral fingerprints of aqueous and hydrothermal deposits and map the geology, composition and stratigraphy of surface features. The instrument will also watch the seasonal variations in Martian dust and ice aerosols, and water content in surface materials -- leading to new understanding of the climate.

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is one of six science instruments on NASA's Mars Reconnaissance Orbiter. Led by The Johns Hopkins University Applied Physics Laboratory, the CRISM team includes expertise from universities, government agencies and small businesses in the United States and abroad.

Technique for ship/wake detection

DOEpatents

Roskovensky, John K [Albuquerque, NM

2012-05-01

An automated ship detection technique includes accessing data associated with an image of a portion of Earth. The data includes reflectance values. A first portion of pixels within the image are masked with a cloud and land mask based on spectral flatness of the reflectance values associated with the pixels. A given pixel selected from the first portion of pixels is unmasked when a threshold number of localized pixels surrounding the given pixel are not masked by the cloud and land mask. A spatial variability image is generated based on spatial derivatives of the reflectance values of the pixels which remain unmasked by the cloud and land mask. The spatial variability image is thresholded to identify one or more regions within the image as possible ship detection regions.

D Reconstruction with a Collaborative Approach Based on Smartphones and a Cloud-Based Server

NASA Astrophysics Data System (ADS)

Nocerino, E.; Poiesi, F.; Locher, A.; Tefera, Y. T.; Remondino, F.; Chippendale, P.; Van Gool, L.

2017-11-01

The paper presents a collaborative image-based 3D reconstruction pipeline to perform image acquisition with a smartphone and geometric 3D reconstruction on a server during concurrent or disjoint acquisition sessions. Images are selected from the video feed of the smartphone's camera based on their quality and novelty. The smartphone's app provides on-the-fly reconstruction feedback to users co-involved in the acquisitions. The server is composed of an incremental SfM algorithm that processes the received images by seamlessly merging them into a single sparse point cloud using bundle adjustment. Dense image matching algorithm can be lunched to derive denser point clouds. The reconstruction details, experiments and performance evaluation are presented and discussed.

A 3D Cloud-Construction Algorithm for the EarthCARE Satellite Mission

NASA Technical Reports Server (NTRS)

Barker, H. W.; Jerg, M. P.; Wehr, T.; Kato, S.; Donovan, D. P.; Hogan, R. J.

2011-01-01

This article presents and assesses an algorithm that constructs 3D distributions of cloud from passive satellite imagery and collocated 2D nadir profiles of cloud properties inferred synergistically from lidar, cloud radar and imager data.

Cloud Computing and Its Applications in GIS

NASA Astrophysics Data System (ADS)

Kang, Cao

2011-12-01

Cloud computing is a novel computing paradigm that offers highly scalable and highly available distributed computing services. The objectives of this research are to: 1. analyze and understand cloud computing and its potential for GIS; 2. discover the feasibilities of migrating truly spatial GIS algorithms to distributed computing infrastructures; 3. explore a solution to host and serve large volumes of raster GIS data efficiently and speedily. These objectives thus form the basis for three professional articles. The first article is entitled "Cloud Computing and Its Applications in GIS". This paper introduces the concept, structure, and features of cloud computing. Features of cloud computing such as scalability, parallelization, and high availability make it a very capable computing paradigm. Unlike High Performance Computing (HPC), cloud computing uses inexpensive commodity computers. The uniform administration systems in cloud computing make it easier to use than GRID computing. Potential advantages of cloud-based GIS systems such as lower barrier to entry are consequently presented. Three cloud-based GIS system architectures are proposed: public cloud- based GIS systems, private cloud-based GIS systems and hybrid cloud-based GIS systems. Public cloud-based GIS systems provide the lowest entry barriers for users among these three architectures, but their advantages are offset by data security and privacy related issues. Private cloud-based GIS systems provide the best data protection, though they have the highest entry barriers. Hybrid cloud-based GIS systems provide a compromise between these extremes. The second article is entitled "A cloud computing algorithm for the calculation of Euclidian distance for raster GIS". Euclidean distance is a truly spatial GIS algorithm. Classical algorithms such as the pushbroom and growth ring techniques require computational propagation through the entire raster image, which makes it incompatible with the distributed nature of cloud computing. This paper presents a parallel Euclidean distance algorithm that works seamlessly with the distributed nature of cloud computing infrastructures. The mechanism of this algorithm is to subdivide a raster image into sub-images and wrap them with a one pixel deep edge layer of individually computed distance information. Each sub-image is then processed by a separate node, after which the resulting sub-images are reassembled into the final output. It is shown that while any rectangular sub-image shape can be used, those approximating squares are computationally optimal. This study also serves as a demonstration of this subdivide and layer-wrap strategy, which would enable the migration of many truly spatial GIS algorithms to cloud computing infrastructures. However, this research also indicates that certain spatial GIS algorithms such as cost distance cannot be migrated by adopting this mechanism, which presents significant challenges for the development of cloud-based GIS systems. The third article is entitled "A Distributed Storage Schema for Cloud Computing based Raster GIS Systems". This paper proposes a NoSQL Database Management System (NDDBMS) based raster GIS data storage schema. NDDBMS has good scalability and is able to use distributed commodity computers, which make it superior to Relational Database Management Systems (RDBMS) in a cloud computing environment. In order to provide optimized data service performance, the proposed storage schema analyzes the nature of commonly used raster GIS data sets. It discriminates two categories of commonly used data sets, and then designs corresponding data storage models for both categories. As a result, the proposed storage schema is capable of hosting and serving enormous volumes of raster GIS data speedily and efficiently on cloud computing infrastructures. In addition, the scheme also takes advantage of the data compression characteristics of Quadtrees, thus promoting efficient data storage. Through this assessment of cloud computing technology, the exploration of the challenges and solutions to the migration of GIS algorithms to cloud computing infrastructures, and the examination of strategies for serving large amounts of GIS data in a cloud computing infrastructure, this dissertation lends support to the feasibility of building a cloud-based GIS system. However, there are still challenges that need to be addressed before a full-scale functional cloud-based GIS system can be successfully implemented. (Abstract shortened by UMI.)

Stellar Debris in the Large Magellanic Cloud

NASA Image and Video Library

2006-12-08

This is a composite image of N49, the brightest supernova remnant in optical light in the Large Magellanic Cloud; the image combines data from the Chandra X-ray Telescope blue and NASA Spitzer Space Telescope red.

Jupiter

NASA Image and Video Library

1998-06-04

This processed color image of Jupiter was produced in 1990 by the U.S. Geological Survey from a Voyager image captured in 1979. Zones of light-colored, ascending clouds alternate with bands of dark, descending clouds. http://photojournal.jpl.nasa.gov/catalog/PIA00343

NASA CloudSat Captures Hurricane Daniel Transformation

NASA Image and Video Library

2006-07-25

Hurricane Daniel intensified between July 18 and July 23rd. NASA new CloudSat satellite was able to capture and confirm this transformation in its side-view images of Hurricane Daniel as seen in this series of images

Rain Floods Central Texas

NASA Image and Video Library

2007-06-28

This image was taken on June 26, 2007, UTC 20:00. In this image an obvious storm hangs over the middle of the United States. Figure 1 shows NASA CloudSat data looking, in profile, at the cloud in this storm.

Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US

USGS Publications Warehouse

Schleeweis, Karen; Goward, Samuel N.; Huang, Chengquan; Dwyer, John L.; Dungan, Jennifer L.; Lindsey, Mary A.; Michaelis, Andrew; Rishmawi, Khaldoun; Masek, Jeffery G.

2016-01-01

Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.

Implementation on Landsat Data of a Simple Cloud Mask Algorithm Developed for MODIS Land Bands

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Wilson, Michael J.; Varnai, Tamas

2010-01-01

This letter assesses the performance on Landsat-7 images of a modified version of a cloud masking algorithm originally developed for clear-sky compositing of Moderate Resolution Imaging Spectroradiometer (MODIS) images at northern mid-latitudes. While data from recent Landsat missions include measurements at thermal wavelengths, and such measurements are also planned for the next mission, thermal tests are not included in the suggested algorithm in its present form to maintain greater versatility and ease of use. To evaluate the masking algorithm we take advantage of the availability of manual (visual) cloud masks developed at USGS for the collection of Landsat scenes used here. As part of our evaluation we also include the Automated Cloud Cover Assesment (ACCA) algorithm that includes thermal tests and is used operationally by the Landsat-7 mission to provide scene cloud fractions, but no cloud masks. We show that the suggested algorithm can perform about as well as ACCA both in terms of scene cloud fraction and pixel-level cloud identification. Specifically, we find that the algorithm gives an error of 1.3% for the scene cloud fraction of 156 scenes, and a root mean square error of 7.2%, while it agrees with the manual mask for 93% of the pixels, figures very similar to those from ACCA (1.2%, 7.1%, 93.7%).

A Sparse Dictionary Learning-Based Adaptive Patch Inpainting Method for Thick Clouds Removal from High-Spatial Resolution Remote Sensing Imagery

PubMed Central

Yang, Xiaomei; Zhou, Chenghu; Li, Zhi

2017-01-01

Cloud cover is inevitable in optical remote sensing (RS) imagery on account of the influence of observation conditions, which limits the availability of RS data. Therefore, it is of great significance to be able to reconstruct the cloud-contaminated ground information. This paper presents a sparse dictionary learning-based image inpainting method for adaptively recovering the missing information corrupted by thick clouds patch-by-patch. A feature dictionary was learned from exemplars in the cloud-free regions, which was later utilized to infer the missing patches via sparse representation. To maintain the coherence of structures, structure sparsity was brought in to encourage first filling-in of missing patches on image structures. The optimization model of patch inpainting was formulated under the adaptive neighborhood-consistency constraint, which was solved by a modified orthogonal matching pursuit (OMP) algorithm. In light of these ideas, the thick-cloud removal scheme was designed and applied to images with simulated and true clouds. Comparisons and experiments show that our method can not only keep structures and textures consistent with the surrounding ground information, but also yield rare smoothing effect and block effect, which is more suitable for the removal of clouds from high-spatial resolution RS imagery with salient structures and abundant textured features. PMID:28914787

A Sparse Dictionary Learning-Based Adaptive Patch Inpainting Method for Thick Clouds Removal from High-Spatial Resolution Remote Sensing Imagery.

PubMed

Meng, Fan; Yang, Xiaomei; Zhou, Chenghu; Li, Zhi

2017-09-15

Cloud cover is inevitable in optical remote sensing (RS) imagery on account of the influence of observation conditions, which limits the availability of RS data. Therefore, it is of great significance to be able to reconstruct the cloud-contaminated ground information. This paper presents a sparse dictionary learning-based image inpainting method for adaptively recovering the missing information corrupted by thick clouds patch-by-patch. A feature dictionary was learned from exemplars in the cloud-free regions, which was later utilized to infer the missing patches via sparse representation. To maintain the coherence of structures, structure sparsity was brought in to encourage first filling-in of missing patches on image structures. The optimization model of patch inpainting was formulated under the adaptive neighborhood-consistency constraint, which was solved by a modified orthogonal matching pursuit (OMP) algorithm. In light of these ideas, the thick-cloud removal scheme was designed and applied to images with simulated and true clouds. Comparisons and experiments show that our method can not only keep structures and textures consistent with the surrounding ground information, but also yield rare smoothing effect and block effect, which is more suitable for the removal of clouds from high-spatial resolution RS imagery with salient structures and abundant textured features.

Stereo Cloud Height and Wind Determination Using Measurements from a Single Focal Plane

NASA Astrophysics Data System (ADS)

Demajistre, R.; Kelly, M. A.

2014-12-01

We present here a method for extracting cloud heights and winds from an aircraft or orbital platform using measurements from a single focal plane, exploiting the motion of the platform to provide multiple views of the cloud tops. To illustrate this method we use data acquired during aircraft flight tests of a set of simple stereo imagers that are well suited to this purpose. Each of these imagers has three linear arrays on the focal plane, one looking forward, one looking aft, and one looking down. Push-broom images from each of these arrays are constructed, and then a spatial correlation analysis is used to deduce the delays and displacements required for wind and cloud height determination. We will present the algorithms necessary for the retrievals, as well as the methods used to determine the uncertainties of the derived cloud heights and winds. We will apply the retrievals and uncertainty determination to a number of image sets acquired by the airborne sensors. We then generalize these results to potential space based observations made by similar types of sensors.

Get Your Head into the Clouds: Using Word Clouds for Analyzing Qualitative Assessment Data

ERIC Educational Resources Information Center

DePaolo, Concetta A.; Wilkinson, Kelly

2014-01-01

Word clouds (or tag clouds) are popular, fun ways to display text data in graphical form; however, we contend that they can also be useful tools in assessment. Using word clouds, instructors can quickly and easily produce graphical depictions of text representing student knowledge. By investigating the patterns of words or phrases, or lack…

First correlated measurements of the shape and light scattering properties of cloud particles using the new Particle Habit Imaging and Polar Scattering (PHIPS) probe

NASA Astrophysics Data System (ADS)

Abdelmonem, A.; Schnaiter, M.; Amsler, P.; Hesse, E.; Meyer, J.; Leisner, T.

2011-10-01

Studying the radiative impact of cirrus clouds requires knowledge of the relationship between their microphysics and the single scattering properties of cloud particles. Usually, this relationship is obtained by modeling the optical scattering properties from in situ measurements of ice crystal size distributions. The measured size distribution and the assumed particle shape might be erroneous in case of non-spherical ice particles. We present here a novel optical sensor (the Particle Habit Imaging and Polar Scattering probe, PHIPS) designed to measure simultaneously the 3-D morphology and the corresponding optical and microphysical parameters of individual cloud particles. Clouds containing particles ranging from a few micrometers to about 800 μm diameter in size can be characterized systematically with an optical resolution power of 2 μm and polar scattering resolution of 1° for forward scattering directions (from 1° to 10°) and 8° for side and backscattering directions (from 18° to 170°). The maximum acquisition rates for scattering phase functions and images are 262 KHz and 10 Hz, respectively. Some preliminary results collected in two ice cloud campaigns conducted in the AIDA cloud simulation chamber are presented. PHIPS showed reliability in operation and produced size distributions and images comparable to those given by other certified cloud particles instruments. A 3-D model of a hexagonal ice plate is constructed and the corresponding scattering phase function is compared to that modeled using the Ray Tracing with Diffraction on Facets (RTDF) program. PHIPS is a highly promising novel airborne optical sensor for studying the radiative impact of cirrus clouds and correlating the particle habit-scattering properties which will serve as a reference for other single, or multi-independent, measurement instruments.

Painted Saturn

NASA Image and Video Library

2014-09-29

Saturn many cloud patterns, swept along by high-speed winds, look as if they were painted on by some eager alien artist in this image from NASA Cassini spacecraft. With no real surface features to slow them down, wind speeds on Saturn can top 1,100 mph (1,800 kph), more than four times the top speeds on Earth. This view looks toward the sunlit side of the rings from about 29 degrees above the ringplane. The image was taken with the Cassini spacecraft wide-angle camera on April 4, 2014 using a spectral filter which preferentially admits wavelengths of near-infrared light centered at 752 nanometers. The view was obtained at a distance of approximately 1.1 million miles (1.8 million kilometers) from Saturn. Image scale is 68 miles (109 kilometers) per pixel. http://photojournal.jpl.nasa.gov/catalog/PIA18280

Venus - Lower-level Nightside Clouds As Seen By NIMS

NASA Technical Reports Server (NTRS)

1990-01-01

These images are two versions of a near-infrared map of lower-level clouds on the night side of Venus, obtained by the Near Infrared Mapping Spectrometer aboard the Galileo spacecraft as it approached the planet February 10, 1990. Taken from an altitude of about 22,000 miles above the planet, at an infrared wavelength of 2.3 microns (about three times the longest wavelength visible to the human eye) the map shows an area of the turbulent, cloudy middle atmosphere some 30-33 miles above the surface, 6-10 miles below the visible cloudtops. With a spatial resolution of about 13 miles, this is the sharpest image ever obtained of the mid-level clouds of Venus. The image to the left shows the radiant heat from the lower atmosphere (about 400 degrees Fahrenheit) shining through the sulfuric acid clouds, which appear as much as 10 times darker than the bright gaps between clouds. This cloud layer is at about - 30 degrees Fahrenheit, at a pressure about 1/2 Earth's atmospheric pressure. This high-resolution map covers a 40- degree-wide sector of the Northern Hemisphere. The several irregular vertical stripes are data dropouts. The right image, a modified negative, represents what scientists believe would be the visual appearance of this mid-level cloud deck in daylight, with the clouds reflecting sunlight instead of blocking out infrared from the hot planet and lower atmosphere. Near the equator, the clouds appear fluffy and blocky; farther north, they are stretched out into East-West filaments by winds estimated at more than 150 mph, while the poles are capped by thick clouds at this altitude. The Near Infrared Mapping Spectrometer (NIMS) on the Galileo spacecraft is a combined mapping (imaging) and spectral instrument. It can sense 408 contiguous wavelengths from 0.7 microns (deep red) to 5.2 microns, and can construct a map or image by mechanical scanning. It can spectroscopically analyze atmospheres and surfaces and construct thermal and chemical maps. Designed and operated by scientists and engineers at the Jet Propulsion Laboratory, NIMS involves 15 scientists in the U.S., England, and France. The Galileo Project is managed for NASA's Office of Space Science and Applications by JPL; its mission is to study the planet Jupiter and its satellites and magnetosphere after multiple gravity-assist flybys at Venus and the Earth.

Characterization of clouds in Titan's tropical atmosphere

USGS Publications Warehouse

Griffith, C.A.; Penteado, P.; Rodriguez, S.; Le, Mouelic S.; Baines, K.H.; Buratti, B.; Clark, R.; Nicholson, P.; Jaumann, R.; Sotin, Christophe

2009-01-01

Images of Titan's clouds, possible over the past 10 years, indicate primarily discrete convective methane clouds near the south and north poles and an immense stratiform cloud, likely composed of ethane, around the north pole. Here we present spectral images from Cassini's Visual Mapping Infrared Spectrometer that reveal the increasing presence of clouds in Titan's tropical atmosphere. Radiative transfer analyses indicate similarities between summer polar and tropical methane clouds. Like their southern counterparts, tropical clouds consist of particles exceeding 5 ??m. They display discrete structures suggestive of convective cumuli. They prevail at a specific latitude band between 8??-20?? S, indicative of a circulation origin and the beginning of a circulation turnover. Yet, unlike the high latitude clouds that often reach 45 km altitude, these discrete tropical clouds, so far, remain capped to altitudes below 26 km. Such low convective clouds are consistent with the highly stable atmospheric conditions measured at the Huygens landing site. Their characteristics suggest that Titan's tropical atmosphere has a dry climate unlike the south polar atmosphere, and despite the numerous washes that carve the tropical landscape. ?? 2009. The American Astronomical Society.

Retrieval of Cloud Properties for Partially Cloud-Filled Pixels During CRYSTAL-FACE

NASA Astrophysics Data System (ADS)

Nguyen, L.; Minnis, P.; Smith, W. L.; Khaiyer, M. M.; Heck, P. W.; Sun-Mack, S.; Uttal, T.; Comstock, J.

2003-12-01

Partially cloud-filled pixels can be a significant problem for remote sensing of cloud properties. Generally, the optical depth and effective particle sizes are often too small or too large, respectively, when derived from radiances that are assumed to be overcast but contain radiation from both clear and cloud areas within the satellite imager field of view. This study presents a method for reducing the impact of such partially cloud field pixels by estimating the cloud fraction within each pixel using higher resolution visible (VIS, 0.65mm) imager data. Although the nominal resolution for most channels on the Geostationary Operational Environmental Satellite (GOES) imager and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra are 4 and 1 km, respectively, both instruments also take VIS channel data at 1 km and 0.25 km, respectively. Thus, it may be possible to obtain an improved estimate of cloud fraction within the lower resolution pixels by using the information contained in the higher resolution VIS data. GOES and MODIS multi-spectral data, taken during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE), are analyzed with the algorithm used for the Atmospheric Radiation Measurement Program (ARM) and the Clouds and Earth's Radiant Energy System (CERES) to derive cloud amount, temperature, height, phase, effective particle size, optical depth, and water path. Normally, the algorithm assumes that each pixel is either entirely clear or cloudy. In this study, a threshold method is applied to the higher resolution VIS data to estimate the partial cloud fraction within each low-resolution pixel. The cloud properties are then derived from the observed low-resolution radiances using the cloud cover estimate to properly extract the radiances due only to the cloudy part of the scene. This approach is applied to both GOES and MODIS data to estimate the improvement in the retrievals for each resolution. Results are compared with the radar reflectivity techniques employed by the NOAA ETL MMCR and the PARSL 94 GHz radars located at the CRYSTAL-FACE Eastern & Western Ground Sites, respectively. This technique is most likely to yield improvements for low and midlevel layer clouds that have little thermal variability in cloud height.

Haze over Beijing

NASA Technical Reports Server (NTRS)

2007-01-01

Thick haze collected over the Beijing region in late March 2007. Earlier that month, the BBC News reported that an international team of scientists had documented how increasing pollution in China led to decreasing rainfall over the region. The Moderate Resolution Imaging Spectroradiometer (MODIS) flying onboard the Aqua satellite captured these images of the Beijing region on March 22, 2007. The top image is a 'true-color' picture, similar to a digital photo. The bottom, 'false-color,' image uses a combination of visible and infrared light to more clearly show vegetation, water, and clouds. Even sparse vegetation appears bright green, while water appears deep blue (bright blue when tinged with sediment). Clouds dominated by water droplets appear white, while clouds made of ice crystals appear light blue. The false-color image highlights water bodies, perhaps aqua-culture ponds, that are all but invisible in the true-color image, especially along the shores of the Bo Hai. While vegetation and water show up more clearly in the false-color image, haze is much more transparent. Although dingy gray haze dominates the true-color picture, it is all but invisible in the false-color view. The haze 'disappears' in the infrared-enhanced image because tiny haze particles do not reflect longer-wavelength infrared light very well, making this type of image useful for distinguishing haze from clouds. The bank of clouds in the upper right corner shows up clearly in both pictures. As China industrializes, factories, power plants, and automobiles all contribute to pollution in the region. In examining pollutants and rainfall, the team of scientists examined records covering more than 50 years, concluding that pollution decreased precipitation at Mount Hua near Xi'an in central China. They concluded that when conditions are so hazy that visibility is reduced to less than 8 kilometers (5 miles), hilly precipitation can drop by 30 to 50 percent. When moist air passes over mountains, it usually cools and forms raindrops, but heavy pollutant concentrations cause the clouds to hang on to their moisture.

Cloud Spirals and Outflow in Tropical Storm Katrina

NASA Technical Reports Server (NTRS)

2005-01-01

On Tuesday, August 30, 2005, NASA's Multi-angle Imaging SpectroRadiometer retrieved cloud-top heights and cloud-tracked wind velocities for Tropical Storm Katrina, as the center of the storm was situated over the Tennessee valley. At this time Katrina was weakening and no longer classified as a hurricane, and would soon become an extratropical depression. Measurements such as these can help atmospheric scientists compare results of computer-generated hurricane simulations with observed conditions, ultimately allowing them to better represent and understand physical processes occurring in hurricanes.

Because air currents are influenced by the Coriolis force (caused by the rotation of the Earth), Northern Hemisphere hurricanes are characterized by an inward counterclockwise (cyclonic) rotation towards the center. It is less widely known that, at high altitudes, outward-spreading bands of cloud rotate in a clockwise (anticyclonic) direction. The image on the left shows the retrieved cloud-tracked winds as red arrows superimposed across the natural color view from MISR's nadir (vertical-viewing) camera. Both the counter-clockwise motion for the lower-level storm clouds and the clockwise motion for the upper clouds are apparent in these images. The speeds for the clockwise upper level winds have typical values between 40 and 45 m/s (144-162 km/hr). The low level counterclockwise winds have typical values between 7 and 24 m/s (25-86 km/hr), weakening with distance from the storm center. The image on the right displays the cloud-top height retrievals. Areas where cloud heights could not be retrieved are shown in dark gray. Both the wind velocity vectors and the cloud-top height field were produced by automated computer recognition of displacements in spatial features within successive MISR images acquired at different view angles and at slightly different times.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously, viewing the entire globe between 82o north and 82o south latitude every nine days. This image covers an area of about 380 kilometers by 1970 kilometers. These data products were generated from a portion of the imagery acquired during Terra orbit 30324 and utilize data from blocks 55-68 within World Reference System-2 path 22.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Science Mission Directorate, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is managed for NASA by the California Institute of Technology.

Correction of thin cirrus effects in AVIRIS images using the sensitive 1.375-micron cirrus detecting channel

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Kaufman, Yorman J.

1995-01-01

Using spectral imaging data acquired with the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) from an ER-2 aircraft at 20 km altitude during various field programs, it was found that narrow channels near the center of the strong 1.38-micrometer water vapor band are very effective in detecting think cirrus clouds. Based on this observation from AVIRIS data, Gao and Kaufman proposed to put a channel centered at 1.375 micrometers with a width of 30 nm on the Moderate Resolution Imaging Spectrometer (MODIS) for remote sensing of cirrus clouds from space. The sensitivity of the 1.375-micrometer MODIS channel to detect thin cirrus clouds during the day time is expected to be one to two orders of magnitude better than the current infrared emission techniques. As a result, much larger fraction of the satellite data is expected to be identified as being covered by cirrus clouds, some of them so thin that their obscuration of the surface is very small. In order to make better studies of surface reflectance properties, thin cirrus effects must be removed from satellite images. Therefore, there is a need to study radiative properties of thin cirrus clouds, so that a strategy for correction or removal of the thin cirrus effects, similar to the correction of atmospheric aerosol effect, can be formed. In this extended abstract, we describe an empirical approach for removing/correcting thin cirrus effects in AVIRIS images using channels near 1.375 microns - one step beyond the detection of cirrus clouds using these channels.