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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

The Earth Model Column Collaboratory (EMC2) v1.1: An Open-Source Ground-Based Lidar and Radar Instrument Simulator and Subcolumn Generator for Large-Scale Models

Climate models are essential for our comprehensive understanding of Earth's atmosphere and can provide critical insights on future changes decades ahead. Because of these critical roles, today's climate models are continuously being developed and evaluated using constraining observations and measurements obtained by satellites, airborne, and ground-based instruments. Instrument simulators can provide a bridge between the measured or retrieved quantities and their sampling in models and field observations while considering instrument sensitivity limitations. Here we present the Earth Model Column Collaboratory (EMC2), an open-source ground-based lidar and radar instrument simulator and subcolumn generator, specifically designed for large-scale models, in particular climate models, but also applicable to high-resolution model output. EMC2 provides a flexible framework enabling direct comparison of model output with ground-based observations, including generation of subcolumns that may statistically represent finer model spatial resolutions. In addition, EMC2 emulates ground-based (and air- or space-borne) measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. The simulator uses either single particle or bulk particle size distribution lookup tables, depending on the selected scheme approach, to perform the forward calculations. To facilitate model evaluation, EMC2 also includes three hydrometeor classification methods, namely, radar- and sounding-based cloud and precipitation detection and classification, lidar-based phase classification, and a Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) lidar simulator emulator. The software is written in Python, is easy to use, and can be straightforwardly customized for different models, radars, and lidars. Following the description of the logic, functionality, features, and software structure of EMC2, we present a case study of highly supercooled mixed-phase cloud based on measurements from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE). We compare observations with the application of EMC2 to outputs from four configurations of the NASA Goddard Institute for Space Studies (GISS) climate model (ModelE3) in single-column model (SCM) mode and from a large-eddy simulation (LES) model. We show that two of the four ModelE3 configurations can form and maintain highly supercooled precipitating cloud for several hours, consistent with observations and LES. While our focus is on one of these ModelE3 configurations, which performed slightly better in this case study, both of these configurations and the LES results post-processed with EMC2 generally provide reasonable agreement with observed lidar and radar variables. As briefly demonstrated here, EMC2 can provide a lightweight and flexible framework for comparing the results of both large-scale and high-resolution models directly with observations, with relatively little overhead and multiple options for achieving consistency with model microphysical or radiation scheme physics.

Earth Model Column Collaboratory↗
NASA NTRS1987

Detection of interstellar PN - The first phosphorus-bearing species observed in molecular clouds

Phosphorus nitride (PN) has been detected in the interstellar medium. The J = 2-1, 3-2, 5-4, and 6-5 rotational lines of this species have been observed toward Orion-KL, and the J = 2-1 transition in Sgr B2 and W51. The PN line profiles in Orion indicate that the molecule's emission arises from the 'plateau' or 'doughnut' region associated with the outflow from IRc2. The species is thus primarily present in hot, dense gas. Column densities derived for PN toward Orion-KL are (3-4) x 10 to the 13th/sq cm, but may be as high as 10 to the 14th/sq cm, if the species is located in a 10-arcsec region. These column densities imply a fractional abundance for PN in the Orion 'plateau' of (1-4) x 10 to the -10th. Such a large abundance for PN is not predicted by quiescent cloud ion-molecule chemistry and suggests that high-temperature processes are responsible for the synthesis of PN in the KL outflow.

Ziurys, L. M.↗
NASA NTRS1990

Silicon chemistry in interstellar clouds

A new model of interstellar silicon chemistry is presented that explains the lack of SiO detections in cold clouds and contains an exponential temperature dependence for the SiO abundance. A key aspect of the model is the sensitivity of SiO production by neutral silicon reactions to density and temperature, which arises from the dependence of the rate coefficients on the population of the excited fine-structure levels of the silicon atom. As part of the explanation of the lack of SiO detections at low temperatures and densities, the model also emphasizes the small efficiencies of the production routes and the correspondingly long times needed to reach equilibrium. Measurements of the abundance of SiO, in conjunction with theory, can provide information on the physical properties of interstellar clouds such as the abundance of oxygen bearing molecules and the depletion of interstellar silicon.

Langer, William D.↗
NASA NTRS1998

Validation of POLDER/ADEOS data using a ground-based lidar network: Preliminary results for semi-transparent and cirrus clouds

At mid and tropical latitudes, cirrus clouds are present more than 50% of the time in satellites observations. Due to their large spatial and temporal coverage, and associated low temperatures, cirrus clouds have a major influence on the Earth-Ocean-Atmosphere energy balance through their effects on the incoming solar radiation and outgoing infrared radiation. At present the impact of cirrus clouds on climate is well recognized but remains to be asserted more precisely, for their optical and radiative properties are not very well known. In order to understand the effects of cirrus clouds on climate, their optical and radiative characteristics of these clouds need to be determined accurately at different scales in different locations i.e. latitude. Lidars are well suited to observe cirrus clouds, they can detect very thin and semi-transparent layers, and retrieve the clouds geometrical properties i.e. altitude and multilayers, as well as radiative properties i.e. optical depth, backscattering phase functions of ice crystals. Moreover the linear depolarization ratio can give information on the ice crystal shape. In addition, the data collected with an airborne version of POLDER (POLarization and Directionality of Earth Reflectances) instrument have shown that bidirectional polarized measurements can provide information on cirrus cloud microphysical properties (crystal shapes, preferred orientation in space). The spaceborne version of POLDER-1 has been flown on ADEOS-1 platform during 8 months (October 96 - June 97), and the next POLDER-2 instrument will be launched in 2000 on ADEOS-2. The POLDER-1 cloud inversion algorithms are currently under validation. For cirrus clouds, a validation based on comparisons between cloud properties retrieved from POLDER-1 data and cloud properties inferred from a ground-based lidar network is currently under consideration. We present the first results of the validation.

Chepfer, H.↗
NASA NTRS2015

Snowfall Rate Retrieval Using Passive Microwave Measurements and Its Applications in Weather Forecast and Hydrology

(AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the follow‐on sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has also been developed. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. It employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derives the probability of snowfall. Cloud properties are retrieved using an inversion method with an iteration algorithm and a two‐stream radiative transfer model. A method adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. The SFR products are being used mainly in two communities: hydrology and weather forecast. Global blended precipitation products traditionally do not include snowfall derived from satellites because such products were not available operationally in the past. The ATMS and AMSU/MHS SFR now provide the winter precipitation information for these blended precipitation products. Weather forecasters mainly rely on radar and station observations for snowfall forecast. The SFR products can fill in gaps where no conventional snowfall data are available to forecasters. The products can also be used to confirm radar and gauge snowfall data and increase forecasters' confidence in their prediction.

Meng, Huan↗
NASA NTRS2014

Sport Transition of JPSS VIIRS Imagery for Night-time Applications

The NASA/Short‐term Prediction, Research, and Transition (SPoRT) Program and NOAA/Cooperative Institute for Research in the Atmosphere (CIRA) work within the NOAA/Joint Polar Satellite System (JPSS) Proving Ground to demonstrate the unique capabilities of the VIIRS instrument. Very similar to MODIS, the VIIRS instrument provides many high‐resolution visible and infrared channels in a broad spectrum. In addition, VIIRS is equipped with a low‐light sensor that is able to detect light emissions from the land and atmosphere as well as reflected sunlight by the lunar surface. This band is referred to as the Day‐Night Band due to the sunlight being used at night to see cloud and topographic features just as one would typically see in day‐time visible imagery. NWS forecast offices that collaborate with SPoRT and CIRA have utilized MODIS imagery in operations, but have longed for more frequent passes of polar‐orbiting data. The VIIRS instrument enhances SPoRT collaborations with WFOs by providing another day and night‐time pass, and at times two additional passes due to its large swath width. This means that multi‐spectral, RGB imagery composites are more readily available to prepare users for their use in GOES‐R era and high‐resolution imagery for use in high‐latitudes is more frequently able to supplement standard GOES imagery within the SPoRT Hybrid GEO‐LEO product. The transition of VIIRS also introduces the new Day‐Night Band capability to forecast operations. An Intensive Evaluation Period (IEP) was conducted in Summer 2013 with a group of "Front Range" NWS offices related to VIIRS night‐time imagery. VIIRS single‐channel imagery is able to better analyze the specific location of fire hotspots and other land features, as well as provide a more true measurement of various cloud and aerosol properties than geostationary measurements, especially at night. Viewed within the SPoRT Hybrid imagery, the VIIRS data allows forecasters to better interpret the more frequent, but coarse GOES Imagery. Night‐time Microphysics and Dust RGB Imagery provides cloud analysis of cloud height, thickness, and composition in order for operational applications such as separating fog from low clouds, dust plume detection, and determining precipitating clouds in radar-void/ blocked regions. The Day‐Night Band has a particular benefit to seeing light from cities, fires, or other emissions as well as the reflection of moonlight off of clouds and smoke plumes, given the right lunar phase and angle. Examples from the VIIRS transition and IEP will be presented.

Fuell, Kevin↗
NASA NTRS1992

Cirrus microphysics and radiative transfer - Cloud field study on 28 October 1986

An analysis of remote-sensing measurements which had detected an inhomogeneous cloud structure, at 6-11 km altitude, in the data acquired during the FIRE 86 experiment in a 75 x 50 km cirrus cloud field, has derived fluxes whose comparison with modeled fluxes imply a modeling-based underestimation of both solar reflectivity/attenuation and downward IR fluxes. Reconciliation of model results with measurements can be achieved either by adding large concentrations of ice crystals or by altering the backscattering properties of ice crystals.

Kinne, Stefan↗
NASA NTRS1982

Detection of pedestal features in dark clouds - Evidence for formation of low mass stars

To assess whether B335 is unique among dark clouds or whether CO-12 pedestal features are quite common, 180 opacity class 5 and 6 Lynds clouds were surveyed. From this set of data, three additional sources were found to have pedestal features. These suggest the presence of embedded low-mass stars, though a hot differentially rotating disk cannot be excluded for B335. Estimates of the mass-loss rate required to produce stellar winds consistent with observations are comparable with mass-loss rates for T Tauri stars. Further, the pedestal feature formation rate is similar to the local low-mass star formation rate.

Frerking, M. A.↗
NASA NTRS1990

Summary of results and conclusions based on analysis of volume imaging and high spectral resolution lidar data acquired during FIRE phase 1, part 1

The collection of long term global statistics on cloud cover may be most easily accomplished with satellite based observations; however, measurements derived from passive satellite retrieval methods must be calibrated and verified by in situ or ground based remote sensor observations. Verification is not straight forward, however, because the highly variable nature of cloud altitude, morphology, and optical characteristics complicates the scaling of point measurements to satellite footprint sized areas. This is particularly evident for cirrus clouds which may be organized on horizontal scales of 10's of meters to 8 km or more, and have optical depths ranging from less than .003 to greater than 3. Cirrus clouds can strongly influence earths' radiative balance, but, because they are often transmissive, cirrus clouds are difficult to detect and characterize from satellite measurements. Because of its precise ranging capabilities, spatial resolution and sensitivity, lidar observations have played an important role in the detection, depiction, and characterization of cirrus clouds. Some of the characteristics of cirrus clouds are summarized which observed the High Spectral Resolution and Volume Imaging Lidars during the phase 1 IFO and ETO periods.

Grund, Christian J.↗
NASA NTRS2009

A Blended Global Snow Product using Visible, Passive Microwave and Scatterometer Satellite Data

A joint U.S. Air Force/NASA blended, global snow product that utilizes Earth Observation System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and QuikSCAT (Quick Scatterometer) (QSCAT) data has been developed. Existing snow products derived from these sensors have been blended into a single, global, daily, user-friendly product by employing a newly-developed Air Force Weather Agency (AFWA)/National Aeronautics and Space Administration (NASA) Snow Algorithm (ANSA). This initial blended-snow product uses minimal modeling to expeditiously yield improved snow products, which include snow cover extent, fractional snow cover, snow water equivalent (SWE), onset of snowmelt, and identification of actively melting snow cover. The blended snow products are currently 25-km resolution. These products are validated with data from the lower Great Lakes region of the U.S., from Colorado during the Cold Lands Processes Experiment (CLPX), and from Finland. The AMSR-E product is especially useful in detecting snow through clouds; however, passive microwave data miss snow in those regions where the snow cover is thin, along the margins of the continental snowline, and on the lee side of the Rocky Mountains, for instance. In these regions, the MODIS product can map shallow snow cover under cloud-free conditions. The confidence for mapping snow cover extent is greater with the MODIS product than with the microwave product when cloud-free MODIS observations are available. Therefore, the MODIS product is used as the default for detecting snow cover. The passive microwave product is used as the default only in those areas where MODIS data are not applicable due to the presence of clouds and darkness. The AMSR-E snow product is used in association with the difference between ascending and descending satellite passes or Diurnal Amplitude Variations (DAV) to detect the onset of melt, and a QSCAT product will be used to map areas of snow that are actively melting.

Foster, James L.↗
NASA NTRS1996

Studies of extra-solar Oort clouds and the Kuiper disk

We are conducting research designed to enhance our understanding of the evolution and detectability of comet clouds and disks. According to 'standard' theory, both the Kuiper Belt and the Oort Cloud are (at least in part) natural products of the planetary accumulation stage of solar system formation. One expects such assemblages to be a common attribute of other solar systems. Therefore, searches for comet disks and clouds orbiting other stars offer a new method for inferring the presence of planetary systems. This project consists of two efforts: (1) observational work to predict and search for the signatures of Oort Clouds and comet disks around other stars; and (2) modelling studies of the formation and evolution of the Kuiper Belt (KB) and similar assemblages that may reside around other stars, including beta Pic.

Stern, S. Alan↗
NASA NTRS1976

Radio detection of interstellar DCO/+/

The J = 1-0 transition of the deuterated formyl ion, DCO(+), has been detected in emission from NGC 2264 and DR 21(OH) and from the cool dust cloud L134. Estimates for the column-density ratios of H(C-13)O(+) to DCO(+) are given for NGC 2264 and DR 21(OH); lower limits for the ratios are given for five other clouds. The DCO(+) detection in L134 provides unique observational evidence in support of chemical fractionation. The L134 results also suggest that the dust clouds may act as repositories for primordial deuterium.

Hollis, J. M.↗
NASA NTRS2004

Cloud Coverage and Height Distribution from the GLAS Polar Orbiting Lidar: Comparison to Passive Cloud Retrievals

The Geoscience Laser Altimeter System (GLAS) began full on orbit operations in September 2003. A main application of the two-wavelength GLAS lidar is highly accurate detection and profiling of global cloud cover. Initial analysis indicates that cloud and aerosol layers are consistently detected on a global basis to cross-sections down to 10(exp -6) per meter. Images of the lidar data dramatically and accurately show the vertical structure of cloud and aerosol to the limit of signal attenuation. The GLAS lidar has made the most accurate measurement of global cloud coverage and height to date. In addition to the calibrated lidar signal, GLAS data products include multi level boundaries and optical depth of all transmissive layers. Processing includes a multi-variable separation of cloud and aerosol layers. An initial application of the data results is to compare monthly cloud means from several months of GLAS observations in 2003 to existing cloud climatologies from other satellite measurement. In some cases direct comparison to passive cloud retrievals is possible. A limitation of the lidar measurements is nadir only sampling. However monthly means exhibit reasonably good global statistics and coverage results, at other than polar regions, compare well with other measurements but show significant differences in height distribution. For polar regions where passive cloud retrievals are problematic and where orbit track density is greatest, the GLAS results are particularly an advance in cloud cover information. Direct comparison to MODIS retrievals show a better than 90% agreement in cloud detection for daytime, but less than 60% at night. Height retrievals are in much less agreement. GLAS is a part of the NASA EOS project and data products are thus openly available to the science community (see http://glo.gsfc.nasa.gov).

Spinhime, J. D.↗
NASA NTRS1974

The scientific justification of a radar scatterometer and a passive microwave system on Seasat-A

The purpose of these two systems is to determine the winds over the ocean. The passive system may also provide data on precipitation over the ocean and sea surface temperature through clouds. They complement each other. The radar scatterometer will sense those sea surface properties that define the winds over the ocean through clouds so thick and so wet that the passive microwave system will have detected only the cloud properties. Both wind speed and direction can be found from the combined data to be obtained.

Pierson, W. J.↗
NASA NTRS1990

Subvisual Cirrus cloud properties derived from a FIRE IFO case study

From the central Wisconsin IFO field at Wausau, the Mobile Polarization Lidar and a surface radiation station from the Lamont-Doherty Geological Observatory observed two very tenuous cirrus clouds on 21 October 1986. The clouds were present just below the height of the tropopause, between -60 to -70 C. The first cloud was not detected visually, and is classified as subvisual cirrus. The second, a relatively narrow cloud band that was probably the remnants of an aircraft contrail, can be termed zenith-subvisual since, although it was invisible in the zenith direction, it could be discerned when viewed at lower elevation angles and also due to strong solar forward-scattering and corona effects. The observations provide an opportunity to assess the threshold cloud optical thickness associated with cirrus cloud visibility. Ruby lidar backscattered signals were converted to isotropic volume backscatter coefficients by applying the pure-molecular scattering assumption just below the cloud base. The backscattering coefficient due to the cloud is then obtained and expressed in relation to the molecular backscattering coefficient in terms of the scattering ratio R. The linear depolarization ratio for the cloud is computed after removing the essentially parallel-polarized scattering contribution from air molecules. The values are also applied to determine the cloud optical thickness through the use of backscatter-to-extinction ratio, and the concentration of cloud particles using the backscattering gain, and the effective diameter of the particles obtained from the analysis of solar corona photographs. The sizes of the particles generating the corona are related to the angular separations between the centers of the red bands and the sun, yielding diameters of approximately 25 microns. The direct and diffuse components of shortwave radiation fluxes, measured by full hemispheric pyranometers, were used to compute the nadir optical thickness of the total atmosphere.

Sassen, Kenneth↗
NASA NTRS2003

Remote Sensing of Liquid Water and Ice Cloud Optical Thickness and Effective Radius in the Arctic: Application of Airborne Multispectral MAS Data

A multispectral scanning spectrometer was used to obtain measurements of the reflection function and brightness temperature of clouds, sea ice, snow, and tundra surfaces at 50 discrete wavelengths between 0.47 and 14.0 microns. These observations were obtained from the NASA ER-2 aircraft as part of the FIRE Arctic Clouds Experiment, conducted over a 1600 x 500 km region of the north slope of Alaska and surrounding Beaufort and Chukchi Seas between 18 May and 6 June 1998. Multispectral images of the reflection function and brightness temperature in 11 distinct bands of the MODIS Airborne Simulator (MAS) were used to derive a confidence in clear sky (or alternatively the probability of cloud), shadow, and heavy aerosol over five different ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (water, ice, or undetermined phase). Finally, the cloud optical thickness and effective radius were derived for both water and ice clouds that were detected during one flight line on 4 June. This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS data in Alaska, is quite capable of distinguishing clouds from bright sea ice surfaces during daytime conditions in the high Arctic. Results of individual tests, however, make it difficult to distinguish ice clouds over snow and sea ice surfaces, so additional tests were added to enhance the confidence in the thermodynamic phase of clouds over the Beaufort Sea. The cloud optical thickness and effective radius retrievals used 3 distinct bands of the MAS, with the newly developed 1.62 and 2.13 micron bands being used quite successfully over snow and sea ice surfaces. These results are contrasted with a MODIS-based algorithm that relies on spectral reflectance at 0.87 and 2.13 micron.

King, Michael D.↗
NASA NTRS1982

Cloud cover from high-resolution scanner data - Detecting and allowing for partially filled fields of view

A new technique is presented for obtaining cloud cover and determining clear sky radiances using high-resolution IR scanner data. The technique, which can be automated, employs the spatial structure of the IR radiance field to identify radiances associated with fields of view that are either free of clouds or completely covered by clouds drawn from one or more distinct layers. The approach is particularly well-suited for determining clear sky radiances over oceans from which sea surface temperatures may be derived. In addition, for single-layered systems, the cloud cover fraction for a given region may be obtained from the clear sky radiance, the completely cloud-covered radiance, and the mean radiance for the region. For such systems the separation of completely covered from partially covered fields of view makes it possible to estimate the errors associated with commonly used threshold techniques for determining cloud cover.

Coakley, J. A., Jr.↗
NASA NTRSDate not supplied

Progress Towards a Common CERES Cloud Mask Algorithm for MODIS and VIIRS: Evaluation using CALIOP Data

For over two decades The Clouds and the Earth’s Radiant Energy System (CERES) project has endeavored to produce a long-term global climate data record for detecting changes in the Earth’s radiation budget and to improve understanding of how clouds contribute to those changes. CERES incorporates cloud information derived from passive narrowband satellite imaging radiometers, and over the course of the project different instruments have contributed to this effort, namely the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS).Cloud properties have been derived from MODIS on the Aqua satellite for CERES since 2002,and VIIRS on the NOAA-20 satellite launched in 2017 will continue the cloud record once Aqua-MODIS reaches the end of its operational lifetime. However, MODIS and VIIRS have different spectral capabilities and characteristics which complicates our ability to seamlessly transition the record from MODIS to VIIRS. This study evaluates some of the recent algorithm modifications incorporated by the CERES Cloud Working Group towards developing a unified cloud mask algorithm for MODIS and VIIRS that utilizes a set of spectral bands common to both instruments. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products are used to evaluate MODIS and VIIRS regional cloud fraction estimates and identify areas where improvements can be made. The cloud mask algorithm relies on computed estimates of cloud-free top-of-atmosphere radiances to differentiate cloudy and cloud-free imager pixels. The unified cloud mask algorithm currently under development uses a reduced number of spectral bands common to both MODIS and VIIRS and so relies on the accuracy of these simulated cloud-free radiances more heavily than predecessor algorithms, i.e., the CERES Edition 4 cloud mask, which use as much spectral information as available on each imager with less consideration for cross-platform consistency. Our validation strategy using CALIOP data is also described. The CALIOP observations are critical for assessing cloud detection accuracies and for independently confirming cloud-free conditions which enables a more robust evaluation of the simulated cloud-free radiances for biases due to factors such as view angle and the spectral dependence of water vapor absorption. These effects are known to differ for the two satellite instruments. Comparisons of MODIS and VIIRS cloud fractions are presented in context with estimates from CALIOP and from the CERES Edition 4 cloud mask algorithm to gauge current progress in developing accurate and consistent MODIS and VIIRS cloud properties for CERES.

CERES↗