Search NASA⌕ Search

SEARCH · Search NASA

Results for “CLOUD DETECTION”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17

The EOS CERES Global Cloud Mask

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.

Berendes, T. A.↗

Ten Years of Cloud Optical and Microphysical Retrievals from MODIS

The MODIS cloud optical properties algorithm (MOD06/MYD06 for Terra and Aqua MODIS, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the "standard" 2.1 11m effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixellevel (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (lD and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).

Platnick, Steven↗

Detection of Multi-Layer and Vertically-Extended Clouds Using A-Train Sensors

The detection of mUltiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). For the first time, we use data from the CloudSat radar to evaluate the results of a multi-layer cloud detection scheme. The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from CloudSat. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (l2kmx24km at nadir) and at the 5kmx5km MODIS resolution used for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of cloudy pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 10% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (approx.20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find higher fractions of vertically-extended clouds over land as compared with ocean, particularly in the tropics and summer hemisphere.

Joiner, J.↗

CO and IRAS detection of an intermediate-velocity cloud

In the course of a radio survey of high-Galactic-latitude clouds, CO emission was detected at the position l = 210.8 deg and b = 63.1 deg with an LSR velocity of -39 km/sec. This molecular cloud constitutes the third one with an unusually large absolute velocity at these latitudes, as compared with the 5.4-km/sec cloud-to-cloud velocity dispersion of the high-latitude molecular clouds. The position is coincident with an H I intermediate-velocity cloud (GHL 11, Verschuur H, OLM 268) and the IR-excess cloud 306 in the list by Desert et al. (1988). This cloud is clearly detected at all four IRAS wavelengths and has warmer colors than the local ISM.

Desert, F.-X.↗

Airborne lidar/radiometric measurements of cirrus cloud parameters and their application to LOWTRAN radiance evaluations

SRI has assembled an airborne lidar/radiometric instrumentation suite for mapping cirrus cloud distribution and analyzing cirrus cloud optical properties. Operation of upward viewing infrared radiometers from an airborne platform provides the optimum method of measuring high altitude cold cloud radiative properties with minimum interference from the thermal emission by the earth's surface and lower atmospheric components. Airborne installed sensors can also operate over large regional areas including water, urban, and mountain surfaces and above lower atmospheric convective clouds and haze layers. Currently available sensors installed on the SRI Queen Air aircraft are illustrated. Lidar and radiometric data records are processed for real time viewing on a color video screen. A cirrus cloud data example is presented as a black and white reproduction of a color display of data at the aircraft altitude of 12,000 ft, the 8 to 14 micron atmospheric radiation background was equivalent to a blackbody temperature of about -60 C and, therefore, the radiometer did not respond strongly to low density cirrus cloud concentrations detected by the lidar. Cloud blackbody temperatures (observed by radiometer) are shown plotted against midcloud temperatures (derived from lidar observed cloud heights and supporting temperature profiles) for data collected on 30 June and 28 July.

Uthe, Edward E.↗

Assessment of Cloud Mask Forecasts from the WRF-Solar Ensemble Prediction System: Preprint

Numerical weather prediction (NWP) models are important tools used by government agencies and the renewable energy enterprise to forecast solar radiation. Cloud prediction, a key process of NWP models, has the highest impact on the accuracy of solar forecasting. This study uses satellite observations from the National Solar Radiation Data Base (NSRDB) to evaluate the cloud mask forecast by the WRF-Solar Ensemble Prediction System (WRF-Solar EPS). Preliminary analysis of the data in 2018 demonstrates the need of further improvement in predicting thin and low-level clouds. The information obtained from this work will be used to enhance the WRF-Solar EPS in reproducing the cloud field over the contiguous U.S. and reducing solar forecasting errors.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Geolocation Assessment Algorithm for CALIPSO Using Coastline Detection

Cloud-Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) is a joint satellite mission between NASA and the French space agency CNES. The investigation will gather long-term, global cloud and aerosol optical and physical properties to improve climate models. The CALIPSO spacecraft is scheduled to launch in 2004 into a 98.2 inclination, 705 km circular orbit approximately 3 minutes behind the Aqua spacecraft. The payload consists of a two-wavelength polarization-sensitive lidar, and two passive imagers operating in the visible (0.645 mm) and infrared (8.7 - 12.0 mm) spectral regions. The imagers are nadir viewing and co-aligned with the lidar. Earth viewing measurements are geolocated to the Earth fixed coordinate system using satellite ephemeris, Earth rotation and geoid, and instrument pointing data. The coastline detection algorithm will assess the accuracy of the CALIPSO geolocation process by analyzing Wide Field Camera (WFC) visible ocean land boundaries. Processing space-time coincident MODIS and WFC scenes with the coastline algorithm will help verify the co-registration requirement with Moderate Resolution Imaging Spectrometer (MODIS) data. This paper quantifies the accuracy of the coastline geolocation assessment algorithm.

Currey, J. Chris↗

Detection of Ice Polar Stratospheric Clouds from Assimilation of Atmospheric Infrared Sounder Data

A novel technique is presented for detection of ice polar stratospheric clouds (PSCs) that form at extremely low temperatures in the lower polar stratosphere during winter. Temperature is a major factor in determining abundance of PSCs, which in turn provide surfaces for heterogeneous chemical reactions leading to ozone loss and radiative cooling. The technique infers the presence of ice PSCs using radiances from the Atmospheric Infrared Sounder (AIRS) in the Goddard Earth Observing System version 5 (GEOS-5) data assimilation system. Brightness temperatures are computed from short-term GEOS-5 forecasts for several hundred AIRS channels, using a radiation transfer module. The differences between collocated AIRS observations and these computed values are the observed-minus-forecast (O-F) residuals in the assimilation system. Because the radiation model assumes clear-sky conditions, we hypothesize that these O-F residuals contain quantitative information about PSCs. This is confirmed using sparse data from the Polar Ozone and Aerosol Measurement (POAM) III occultation instrument. The analysis focuses on 0-F residuals for the 6.79pm AIRS moisture channel. At coincident locations, when POAM III detects ice clouds, the AIRS O-F residuals for this channel are lower than -2K. When no ice PSCs are evident in POAM III data, the AIRS 0-F residuals are larger. Given this relationship, the high spatial density of AIRS data is used to construct maps of regions where 0-F residuals are lower than -2K, as a proxy for ice PSCs. The spatial scales and spatio-temporal variations of these PSCs in the Antarctic and Arctic are discussed on the basis of these maps.

Stajner, Ivanka↗

Detection of absorption by H2 in molecular clouds: A direct measurement of the H2:CO ratio

Vibrational absorption by H2 and CO has been searched for toward infrared sources embedded in molecular clouds. H2 was detected toward NGC 2024 IRS 2 and possibly toward NGC 2264 (GL 989). CO was detected toward both sources. The results are consistent with the H2 ortho:para ratio being equilibrated at the cloud temperature. Toward NGC 2024, H2:CO = (3700(sub -2600)(sup +3100)) (2 sigma limits), and toward NGC 2264, H2:CO less than 6000. Approximately one-third of all carbon is in gas-phase CO.

Lacy, J. H.↗

Far-infrared observations of shocked CO in Orion

The J = 27-26 and J = 30-29 transitions of CO have been detected in the Orion molecular cloud. These detections, together with an improved measurement of the J = 21-20 transition, allow estimation of the temperature and density of the shocked material and the fractional abundance of CO. By solving the equations of detailed balance for J less than or equal to 50 and fitting the data to a two-component model consistent with earlier 2-micron and 12-micron H2 observations, it is shown that the hot (2000 K) component has a density of approximately 1.0 x 10 to the 6th/cu cm, while the cooler component lies in the range of 400-1000 K and is 2-5 times more dense. Approximately 25% of the carbon is in the form of CO. The spatial extent of the hot CO has also been examined by observing the J = 21-20 transition at a number of positions, and it is found to be distributed similarly to the H2 lines. In addition, a search for J = 21-20 and J = 22-21 CO emission from six other sources has resulted in 3-standard-deviation upper limits of a factor of 10 below the intensity of the Orion lines.

Storey, J. W. V.↗

Observation of the HH 1 and 2 region with IRAS

Infrared Astronomical Satellite (IRAS) observations of the region in Orion containing HH 1 and 2 reveal for the first time the large-scale distribution of newly formed stars. New infrared sources discovered in these observations are discussed, and attempts are made to untangle the complex infrared morphology of this field. A major finding of this study is that HH 1 is near the peak of an intense and broad plateau of 60 and 100 micron emission that spatially corresponds well with the boundaries of a previously detected molecular cloud. Other findings include the detection of an emitting circum-HH object dust complex around HH 2, 25 micron emission associated with the putative HH 1 and 2 exciting source discovered with the VLA, a new luminous far-infrared source, and numerous infrared source complexes, some in blank optical fields and others in fields containing optical emission-line stars.

Pravdo, Steven H.↗

Understanding of Jupiter's Atmosphere After the Galileo Probe Entry

Instruments on the Galileo probe measured composition, cloud properties, thermal structure. winds, radiative energy balance, and electrical properties of the Jovian atmosphere. As expected the probe results confirm some expectations about Jupiter's atmosphere, refute others, and raise new questions which still remain unanswered. This talk will concentrate on those aspects of the probe observations which either raised new questions or remain unresolved. The Galileo probe observations of composition and clouds provided some of the biggest surprises of the mission. Helium abundance measured by the probe differed significantly from the remote sensing derivations from Voyager. discrepancy between the Voyager helium abundance determinations for Jupiter and the Galileo probe value have now led to a considerably increased helium determination for Saturn. Global abundance of N in the form of ammonia was observed to be supersolar by approximately the same factor as carbon, in contrast to expectations that C/N would be significantly larger than solar. This has implications for the formation and evolution of Jupiter. The cloud structure was not what was generally anticipated, even though most previous remote sensing results below the uppermost cloud referred to 5 micron hot spots, local regions with reduced cloud opacity. The Galileo probe descended in one of these hot spots. Only a tenuous, presumed ammonium hydrosulfide, cloud was detected, and no significant water cloud or super-solar water abundance was measured. The mixing ratios as a function of depth for the condensibles ammonia, hydrogen sulfide, and water, exhibited no apparent correlation with either condensation levels or with each other, an observation that is still a puzzle, although there are now dynamical models of hot spots which show promise in being able to explain such behavior. Probe tracked zonal winds show that wind magnitude increases with depth to pressures of about 4 bars, with the winds extending to at least as deep as the probe made measurements, 22 bars. Models of hot spot dynamics raise the possibility that the variation with depth of the probe measured zonal winds between 0.4 and 4 bars reflect the dynamics of the hot spot rather than the global wind pattern. Galileo upper atmosphere measurements established that there is a sharp temperature rise with altitude between about 350 and 800 km above the 1 bar pressure level, with the upper atmosphere reaching, temperatures near 900 K. The energy sources for this upper atmosphere heating are not clearly established, but various mechanisms have been proposed. These and other aspects of the Galileo probe data will be discussed.

Young, Richard E.↗

Understanding of Jupiter's Atmosphere after the Galileo Probe Entry

Instruments on the Galileo probe measured composition, cloud properties, thermal structure, winds, radiative energy balance, and electrical properties of the Jovian atmosphere. As expected the probe results confirm some expectations about Jupiter's atmosphere, refute others, and raise new questions which still remain unanswered. This talk will concentrate on those aspects of the probe observations which either raised new questions or remain unresolved. The Galileo probe observations of composition and clouds provided some of the biggest surprises of the mission. Helium abundance measured by the probe differed significantly from the remote sensing derivations from Voyager. Discrepancy between the Voyager helium abundance determinations for Jupiter and the Galileo probe value have now led to a considerably increased helium determination for Saturn. Global abundance of N in the form of ammonia was observed to be super-solar by approximately the same factor as carbon, in contrast to expectations that C/N would be significantly larger than solar. This has implications for the formation and evolution of Jupiter. The cloud structure was not what was generally anticipated, even though most previous remote sensing results below the uppermost cloud referred to 5 micron hot spots, local regions with reduced cloud opacity. The Galileo probe descended in one of these hot spots. Only a tenuous, presumed ammomium hydrosulfide, cloud was detected, and no significant water cloud or super-solar water abundance was measured. The mixing ratios as a function of depth for the condensibles ammonia, hydrogen sulfide, and water, exhibited no apparent correlation with either condensation levels or with each other, an observation that is still a puzzle, although there are now dynamical models of hot spots which show promise in being able to explain such behavior. Probe tracked zonal winds show that wind magnitude increases with depth to pressures of about 4 bars, with the winds extending to at least as deep as the probe made measurements, 22 bars. Models of hot spot dynamics raise the possibility that the variation with depth of the probe measured zonal winds between 0.4 and 4 bars reflect the dynamics of the hot spot rather than the global wind pattern. Galileo upper atmosphere measurements established that there is a sharp temperature rise with altitude between about 350 and 800 km above the 1 bar pressure level, with the upper atmosphere reaching temperatures near 900 K. The energy sources for this upper atmosphere heating are not clearly established, but various mechanisms have been proposed. These and other aspects of the Galileo probe data will be discussed.

Fonda, Mark↗

Current and Future Applications of Multispectral (RGB) Satellite Imagery for Weather Analysis and Forecasting Applications

Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low ]Earth orbits. The NASA Short ]term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA fs Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channels available from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard METEOSAT ]9. This broader suite includes products that discriminate between air mass types associated with synoptic ]scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES ]R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar ]Orbiting Partnership (S ]NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross ]track Infrared Sounder (CrIS), and the Advanced Technology Microwave Sounder (ATMS), which have unrivaled spectral and spatial resolution, as precursors to the JPSS era (i.e., the next generation of polar orbiting satellites. New applications from VIIRS extend multispectral composites available from MODIS and SEVIRI while adding new capabilities through incorporation of additional CrIS channels or information from the Near Constant Contrast or gDay ]Night Band h, which provides moonlit reflectance from clouds and detection of fires or city lights. This presentation will present a review of SPoRT, CIRA, and NRL collaborations regarding multispectral satellite imagery and recent applications within the operational forecasting environment

Molthan, Andrew L.↗

Positive cloud-to-ground lightning detection by a direction-finder network

Consideration is given to the ability of an automatic direction-finder network to identify cloud-to-ground flashes that effectively lower positive charge to the ground (+CG flashes). Records from an extremely low frequency system are examined to determine whether or not 340 +CG flashes detected by the network have coincident waveforms characteristic of +CG flashes. It is found that false detection in the system is negligible for +CG flashes with range-normalized amplitudes of at least 50 direction-finder units. Also, it is shown that no more than about 15 percent of the +CG flashes detected by the system at smaller amplitudes are false detections.

Macgorman, Donald R.↗

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

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.

Minnis, Patrick↗

Near-Real-Time Satellite Cloud Products for Icing Detection and Aviation Weather over the USA

A set of physically based retrieval algorithms has been developed to derive from multispectral satellite imagery a variety of cloud properties that can be used to diagnose icing conditions when upper-level clouds are absent. The algorithms are being applied in near-real time to the Geostationary Operational Environmental Satellite (GOES) data over Florida, the Southern Great Plains, and the midwestern USA. The products are available in image and digital formats on the world-wide web. The analysis system is being upgraded to analyze GOES data over the CONUS. Validation, 24-hour processing, and operational issues are discussed.

Minnis, Patrick↗

A Simplified Approach to Cloud Masking with VIIRS in the S-NPP/JPSS Era

The quantitative detection of clouds in satellite imagery has a number of important applications in weather analysis. The proper interpretation of satellite imagery for improved situational awareness depends on knowing where the clouds are at all times of the day. Additionally, many products derived from infrared measurements need accurate cloud information to mask out regions where retrieval of geophysical parameters in the atmosphere or on the surface are not possible. Thus, the accurate detection of the presence of clouds in satellite imagery on a global basis is important to the product developers and the operational weather community to support their decision‐making process. This abstract describes an application of a two‐channel bispectral composite threshold (BCT) approach applied to VIIRS imagery. The simplified BCT approach uses only the 10.76 and 3.75 micrometer spectral channels in two spectral tests; a straightforward infrared threshold test with the longwave channel and a shortwave minus longwave channel difference test. The key to the success of this approach as demonstrated in past applications to GOES and MODIS data is the generation of temporally and spatially dependent thresholds used in the tests from a previous number of days at similar observations to the current data. The presentation will present an overview of the approach and intercomparison results with other satellites, methods, and against verification data.

Jedlovec, Gary J.↗