Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “remote sensing of clouds”

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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Cloud Physics Lidar Measurements During the SAFARI-2000 Field Campaign

A new remote sensing instrument, the Cloud Physics Lidar (CPL) has been built for use on the ER-2 aircraft. The first deployment for CPL was the SAFARI-2000 field campaign during August-September 2000. The CPL is a three-wavelength lidar designed for studies of cirrus, subvisual cirrus, and boundary layer aerosols. The CPL utilizes a high repetition rate, low pulse energy laser with photon counting detectors. A brief description of the CPL instrument will be given, followed by examples of CPL data products. In particular, examples of aerosol backscatter, including boundary layer smoke and cirrus clouds will be shown. Resulting optical depth estimates derived from the aerosol measurements will be shown. Comparisons of the CPL optical depth and optical depth derived from microPulse Lidar and the AATS-14 sunphotomer will be shown.

McGill, Matthew↗
NASA NTRS1994

Mesoscale Temperature Fluctuations and Polar Stratospheric Clouds

Using both remote sensing measurements of temperature fluctuations on isentropic surfaces and insitu measurements, we show that even high resolution trajectory calculations seriously understimate the rate of change of temperature experienced by air parcels.

Polar↗
NASA NTRS2003

The Cloud Radar System

Improvement in our understanding of the radiative impact of clouds on the climate system requires a comprehensive view of clouds including their physical dimensions, dynamical generation processes, and detailed microphysical properties. To this end, millimeter vave radar is a powerful tool by which clouds can be remotely sensed. The NASA Goddard Space Flight Center has developed the Cloud Radar System (CRS). CRS is a highly sensitive 94 GHz (W-band) pulsed-Doppler polarimetric radar that is designed to fly on board the NASA high-altitude ER-2 aircraft. The instrument is currently the only millimeter wave radar capable of cloud and precipitation measurements from above most all clouds. Because it operates from high-altitude, the CRS provides a unique measurement perspective for cirrus cloud studies. The CRS emulates a satellite view of clouds and precipitation systems thus providing valuable measurements for the implementation and algorithm validation for the upcoming NASA CloudSat mission that is designed to measure ice cloud distributions on the global scale using a spaceborne 94 GHz radar. This paper describes the CRS instrument and preliminary data from the recent Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE). The radar design is discussed. Characteristics of the radar are given. A block diagram illustrating functional components of the radar is shown. The performance of the CRS during the CRYSTAL-FACE campaign is discussed.

Racette, Paul↗
NASA NTRS2004

3D Radiative Transfer in Cloudy Atmospheres

3D cloud radiative community has matured enough to prepare a volume on 3D radiative transfer in cloudy atmosphere that will be published by Springer-Verlag this year. Many leading 3D radiative transfer scientists are amongst the co-authors of the book. The book starts with the basic 3D radiative transfer problem, describes its solutions and models, discusses the effects of cloud inhomogeneity for remote sensing, addresses climate problems in realistic atmosphere and studies cloud-vegetation interactions.

Marshak, Alexander↗
NASA NTRS2014

Millimeter- and Submillimeter-Wave Remote Sensing Using Small Satellites

Cloud ice properties and processes play fundamental roles in atmospheric radiation and precipitation. Limited knowledge and poor representation of clouds in global climate models have led to large uncertainties about cloud feedback processes under climate change. Ice clouds have been used as a tuning parameter in the models to force agreement with observations of the radiation budget at the top of the atmosphere, and precipitation at the bottom. The lack of ice cloud measurements has left the cloud processes at intermediate altitudes unconstrained. Millimeter (mm) and submillimeter (submm)-wave radiometry is widely recognized for its potential to fill the cloud measurement gap in the middle and upper troposphere. Analyses have shown that channels from 183900 GHz offer good sensitivity to ice cloud scattering and can provide ice water path (IWP) products to an accuracy of 25 by simultaneously retrieving ice particle size (Dme) and IWP. Therefore, it is highly desirable to develop a cost-effective, compact mm/submm-wave instrument for cloud observations that can be deployed on future small satellites.This paper presents a conceptual study for a mm/submm-wave instrument for multispectral measurements of ice clouds. It discusses previous work at these frequencies by NASA Goddard Space Flight Center (GSFC) and the current instrument study, as well as receiver architectures and their anticipated performance. And finally, it describes a microsatellite prototype intended for use with this mm/submm-wave instrument.

small satellites↗
NASA NTRS2010

Comparison of the MODIS Collection 5 Multilayer Cloud Detection Product with CALIPSO

CALIPSO, launched in June 2006, provides global active remote sensing measurements of clouds and aerosols that can be used for validation of a variety of passive imager retrievals derived from instruments flying on the Aqua spacecraft and other A-Train platforms. The most recent processing effort for the MODIS Atmosphere Team, referred to as the Collection 5 scream, includes a research-level multilayer cloud detection algorithm that uses both thermodynamic phase information derived from a combination of solar and thermal emission bands to discriminate layers of different phases, as well as true layer separation discrimination using a moderately absorbing water vapor band. The multilayer detection algorithm is designed to provide a means of assessing the applicability of 1D cloud models used in the MODIS cloud optical and microphysical product retrieval, which are generated at a 1 km resolution. Using pixel-level collocations of MODIS Aqua, CALIOP, we investigate the global performance of multilayer cloud detection algorithms (and thermodynamic phase).

Platnick, Steven↗
NASA NTRS1990

Lidar cloud studies for FIRE and ECLIPS

Optical remote sensing measurements of cirrus cloud properties were collected by one airborne and four ground-based lidar systems over a 32 h period during this case study from the First ISCCP (International Satellite Cloud Climatology Program) Regional Experiment (FIRE) Intensive Field Observation (IFO) program. The lidar systems were variously equipped to collect linear depolarization, intrinsically calibrated backscatter, and Doppler velocity information. Data presented describe the temporal evolution and spatial distribution of cirrus clouds over an area encompassing southern and central Wisconsin. The cirrus cloud types include: dissipating subvisual and thin fibrous cirrus cloud bands, an isolated mesoscale uncinus complex (MUC), a large-scale deep cloud that developed into an organized cirrus structure within the lidar array, and a series of intensifying mesoscale cirrus cloud masses. Although the cirrus frequently developed in the vertical from particle fall-streaks emanating from generating regions at or near cloud tops, glaciating supercooled (-30 to -35 C) altocumulus clouds contributed to the production of ice mass at the base of the deep cirrus cloud, apparently even through riming, and other mechanisms involving evaporation, wave motions, and radiative effects are indicated. The generating regions ranged in scale from approximately 1.0 km cirrus uncinus cells, to organized MUC structures up to approximately 120 km across.

Sassen, Kenneth↗
NASA NTRS1986

Effects of instrument characteristics on cloud properties retrieved from satellite imagery data

The relationships between sensor resolution and derived cloud properties in satellite remote sensing were studied by comparisons of cloud characteristics determined by spatial coherence analysis of AVHRR and GOES data. The latter data were simulated from 11 microns AVHRR data and were assigned a resolution (8 sq km) half that of the AVHRR. Day and nighttime passes were considered for single-layer maritime cloud systems. Sample radiance vs local standard deviation plots of 1024 points are provided for the same area from AVHRR and GOES-East sensors, demonstrating a qualitative agreement.

Baldwin, D. G.↗
NASA NTRS1990

Application of remote sensing in tropical forests

Cloud cover in tropical humid forests can pose serious operational constraints on Landsat TM and SPOT HRV instrumentation, given their respective orbital frequencies of 16 and 26 days. SAR data intrinsically precludes such problems; the increase of data acquisition frequency to daily rates, as with the NOAA AVHRR instrument, also bears consideration. It is deemed essential that SAR data-related research be expedited, in order to ascertain inherent SAR information for tropical forests in a timely and cost-effective manner.

Joyce, Armond T.↗
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 NTRS1997

Subsonic Aircraft Contrail and Cloud Effects Special Study (SUCCESS)

During recent years interest in the impact of commercial aircraft on the climate has increased. Aircraft might impact climate in a number of ways. Contrails are clearly a direct radiative forcing mechanism. Exhaust emissions, principally soot and sulfate, might indirectly force the climate by modifying the radiative properties of cirrus clouds. The SUCCESS program was carried out to investigate these issues. It also has several other goals including: better understanding the emissions from aircraft, better understanding the formation of cirrus clouds: better understanding the radiative properties of contrails and clouds and their remote sensing; better understanding the heterogeneous chemistry in the upper atmosphere; and developing new instruments of importance to atmospheric chemistry and cloud physics. SUCCESS took place during April and May of 1997. The NASA DC-8, ER-2, T-39, and 757 aircraft were used as in situ sampling, remote sensing, near field sampling, and emission sources respectively. Most of the operations occurred near the DOE's Atmospheric Radiation Measurement Site in Northern Oklahoma. The DOE operated several other aircraft so that on some days as many as six research aircraft flew together. Numerous new instruments functioned during the mission. This talk will present an overview of SUCCESS from the operational point of view, and provide some of the overall scientific highlights.

Toon, O.B.↗
NASA NTRS1997

Subsonic Aircraft Contrail and Cloud Effects Special Study (SUCCESS)

During recent years interest in the impact of commercial aircraft on the climate has increased. Aircraft might impact climate in a number of ways. Contrails are clearly a direct radiative forcing mechanism. Exhaust emissions, principally soot and sulfate, might indirectly radiative force the climate by modifying the properties of cirrus clouds. The SUCCESS program was carried out to investigate these issues. It also had several other goals including: better understanding the emissions from aircraft, better understanding the formation of cirrus clouds: better understanding the radiative properties of contrail and clouds and their remote sensing; better understanding the heterogeneous chemistry in the upper atmosphere; and developing new instruments of importance to atmospheric chemistry and cloud physics. SUCCESS took place during April and May of 1996. The NASA DC-8, ER-2, T-39, and 757 aircraft were used as in situ sampling, remote sensing, near field sampling, and emission sources respectively. Most of the operations occurred near the DOE's Atmospheric Radiation Measurement Site in Northern Oklahoma. The DOE operated several other aircraft so that on some days as many as six research aircraft operated together. Numerous new instruments operated during the mission. This talk will present an overview of SUCCESS from the operational point of view, and provide some of the overall scientific highlights.

Toon, O. B.↗
NASA NTRS2012

Remote Sensing of Tropical Ecosystems: Atmospheric Correction and Cloud Masking Matter

Tropical rainforests are significant contributors to the global cycles of energy, water and carbon. As a result, monitoring of the vegetation status over regions such as Amazonia has been a long standing interest of Earth scientists trying to determine the effect of climate change and anthropogenic disturbance on the tropical ecosystems and its feedback on the Earth's climate. Satellite-based remote sensing is the only practical approach for observing the vegetation dynamics of regions like the Amazon over useful spatial and temporal scales, but recent years have seen much controversy over satellite-derived vegetation states in Amazônia, with studies predicting opposite feedbacks depending on data processing technique and interpretation. Recent results suggest that some of this uncertainty could stem from a lack of quality in atmospheric correction and cloud screening. In this paper, we assess these uncertainties by comparing the current standard surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4 and MYD13A2 - Vegetation Index) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to results obtained from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. MAIAC uses a new cloud screening technique, and novel aerosol retrieval and atmospheric correction procedures which are based on time-series and spatial analyses. Our results show considerable improvements of MAIAC processed surface reflectance compared to MYD09/MYD13 with noise levels reduced by a factor of up to 10. Uncertainties in the current MODIS surface reflectance product were mainly due to residual cloud and aerosol contamination which affected the Normalized Difference Vegetation Index (NDVI): During the wet season, with cloud cover ranging between 90 percent and 99 percent, conventionally processed NDVI was significantly depressed due to undetected clouds. A smaller reduction in NDVI due to increased aerosol levels was observed during the dry season, with an inverse dependence of NDVI on aerosol optical thickness (AOT). NDVI observations processed with MAIAC showed highly reproducible and stable inter-annual patterns with little or no dependence on cloud cover, and no significant dependence on AOT (p less than 0.05). In addition to a better detection of cloudy pixels, MAIAC obtained about 20-80 percent more cloud free pixels, depending on season, a considerable amount for land analysis given the very high cloud cover (75-99 percent) observed at any given time in the area. We conclude that a new generation of atmospheric correction algorithms, such as MAIAC, can help to dramatically improve vegetation estimates over tropical rain forest, ultimately leading to reduced uncertainties in satellite-derived vegetation products globally.

tropical ecosystems↗
NASA NTRS2012

Origin, Transport, and Vertical Distribution of Atmospheric Polluntants over the Northern Sourth China Sea During the 7-SEAS-Dongsha Experiment

During the spring of 2010, comprehensive in situ measurements were made for the first time on a small atoll (Dongsha Island) in the northern South China Sea (SCS), a key region of the 7-SEAS (the Seven South East Asian Studies) program. This paper focuses on characterizing the source origins, transport processes, and vertical distributions of the Asian continental outflows over the region, using measurements including mass concentration, optical properties, hygroscopicity, and vertical distribution of the aerosol particles, as well as the trace gas composition. Cluster analysis of backward trajectories classified 52% of the air masses arriving at ground level of Dongsha Island as having a continental origin, mainly from northern China to the northern SCS, passing the coastal area and being confined in the marine boundary layer (0-0.5 km). Compared to aerosols of oceanic origin, the fine mode continental aerosols have a higher concentration, extinction coefficient, and single-scattering albedo at 550 nm (i.e., 19 vs. 14 microg per cubic meter in PM(sub 2.5); 77 vs. 59 M per meter in beta(sub e); and 0.94 vs. 0.90 in omega, respectively). These aerosols have a higher hygroscopicity (f at 85% RH = 2.1) than those in the upwind inland regions, suggesting that the aerosols transported to the northern SCS were modified by the marine environment. In addition to the near-surface aerosol transport, a significant upper-layer (3-4 km) transport of biomass-burning aerosols was observed. Our results suggest that emissions from both China and Southeast Asia could have a significant impact on the aerosol loading and other aerosol properties over the SCS. Furthermore, the complex vertical distribution of aerosols-coinciding-with-clouds has implications for remote-sensing observations and aerosol-cloud-radiation interactions.

pollutants↗
NASA NTRS2013

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters: Equivalent Sensor Radiance Formulation - Part 1

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Simulations↗
NASA NTRS1986

Pattern recognition of satellite cloud imagery for improved weather prediction

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.

Gautier, Catherine↗