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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Satellite discrimination of snow/cloud surfaces

Differentiation between cloud cover and snow surfaces using remotely sensed data is complicated by the similarity of their radiative temperatures, and also by their similar reflectances at visible wavelengths. A method of cloud analysis over snow-covered regions is presented, using 1.51-1.63 micron data from an experimental sensor on board a U.S. Air Force Defense Meteorological Satellite Program platform. At these wavelengths, snow appears relatively 'black' while clouds are highly reflective. The spatial structure of the 1.51-1.63 micron reflectivity fields over a continuous snow surface are examined. Plots of mean reflectance against coefficients of variation for 4 x 4 pixel areas reveals a cluster of points have low reflectivity and low variability, corresponding to snow-covered (cloud free) areas, and a similar cluster with high reflectances corresponding to 100 per cent cloud cover. For the case of a single layered cloud, the radiances associated with partially filled fields of view are also inferred.

Crane, R. G.↗
NASA NTRS2007

Future of Land Remote Sensing: What is Needed

A viewgraph presentation describing the future of land remote sensing and the new technologies needed for clear views of the Earth is shown. The contents include: 1) Viewing the Earth; 2) Multi-Imagery; 3) May Missions and Sensors; 4) What is Needed; 5) Things to Think About; 6) Global Land Remote Sensing in Landsat 7 Era; 7) Seasonality; 8) Cloud Contamination; 9) NRC Decadal Study; 10) Atmospheric Attenuation; 11) Geo-Registration; 12) Orthorectification Required; 13) Band Registration with OLI; and 14) Things to Do. A viewgraph presentation describing the future of land remote sensing and the new technologies needed for clear views of the Earth is shown. The contents include: 1) Viewing the Earth; 2) Multi-Imagery; 3) May Missions and Sensors; 4) What is Needed; 5) Things to Think About; 6) Global Land Remote Sensing in Landsat 7 Era; 7) Seasonality; 8) Cloud Contamination; 9) NRC Decadal Study; 10) Atmospheric Attenuation; 11) Geo-Registration; 12) Orthorectification Required; 13) Band Registration with OLI; and 14) Things to Do.

Goward, Samuel N.↗
NASA NTRS2008

Summertime Coincident Observations of Ice Water Path in the Visible/Near-IR, Radar, and Microwave Frequencies

Accurate representation of the physical and radiative properties of clouds in climate models continues to be a challenge. At present, both remote sensing observations and modeling of microphysical properties of clouds rely heavily on parameterizations or assumptions on particle size distribution (PSD) and cloud phase. In this study, we compare Ice Water Path (IWP), an important physical and radiative property that provides the amount of ice present in a cloud column, using measurements obtained via three different retrieval strategies. The datasets we use in this study include Visible/Near-IR IWP from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument flying aboard the Aqua satellite, Radar-only IWP from the CloudSat instrument operating at 94 GHz, and NOAA/NESDIS operational IWP from the 89 and 157 GHz channels of the Microwave Humidity Sounder (MHS) instrument flying aboard the NOAA-18 satellite. In the Visible/Near-IR, IWP is derived from observations of optical thickness and effective radius. CloudSat IWP is determined from measurements of cloud backscatter and assumed PSD. MHS IWP retrievals depend on scattering measurements at two different, non-water absorbing channels, 89 and 157 GHz. In order to compare IWP obtained from these different techniques and collected at different vertical and horizontal resolutions, we examine summertime cases in the tropics (30S - 30N) when all 3 satellites are within 4 minutes of each other (approximately 1500 km). All measurements are then gridded to a common 15 km x 15 km box determined by MHS. In a grid box comparison, we find CloudSat to report the highest IWP followed by MODIS, followed by MHS. In a statistical comparison, probability density distributions show MHS with the highest frequencies at IWP of 100-1000 g/m(exp 2) and CloudSat with the longest tail reporting IWP of several thousands g/m(exp 2). For IWP greater than 30 g/m(exp 2), MODIS is consistently higher than CloudSat, and it is higher at the lower IWPs but lower at the higher IWPs that overlap with MHS. Some of these differences can be attributed to the limitations of the measuring techniques themselves, but some can result from the assumptions made in the algorithms that generate the IWP product. We investigate this issue by creating categories based on various conditions such as cloud type, precipitation presence, underlying liquid water content, and surface type (land vs. ocean) and by comparing the performance of the IWP products under each condition.

Pittman, Jasna V.↗
NASA NTRS2008

Application of the CloudSat and NEXRAD Radars Toward Improvements in High Resolution Operational Forecasts

As computational power increases, operational forecast models are performing simulations with higher spatial resolution allowing for the transition from sub-grid scale cloud parameterizations to an explicit forecast of cloud characteristics and precipitation through the use of single- or multi-moment bulk water microphysics schemes. investments in space-borne and terrestrial remote sensing have developed the NASA CloudSat Cloud Profiling Radar and the NOAA National Weather Service NEXRAD system, each providing observations related to the bulk properties of clouds and precipitation through measurements of reflectivity. CloudSat and NEXRAD system radars observed light to moderate snowfall in association with a cold-season, midlatitude cyclone traversing the Central United States in February 2007. These systems are responsible for widespread cloud cover and various types of precipitation, are of economic consequence, and pose a challenge to operational forecasters. This event is simulated with the Weather Research and Forecast (WRF) Model, utilizing the NASA Goddard Cumulus Ensemble microphysics scheme. Comparisons are made between WRF-simulated and observed reflectivity available from the CloudSat and NEXRAD systems. The application of CloudSat reflectivity is made possible through the QuickBeam radiative transfer model, with cautious application applied in light of single scattering characteristics and spherical target assumptions. Significant differences are noted within modeled and observed cloud profiles, based upon simulated reflectivity, and modifications to the single-moment scheme are tested through a supplemental WRF forecast that incorporates a temperature dependent snow crystal size distribution.

Molthan, A. L.↗
NASA NTRS2018

Organic Ices in Titan's Stratosphere

Titan’s stratospheric ice clouds are by far the most complex of any observed in the solar system, with over a dozen organic vapors condensing out to form a suite of pure and co-condensed ices, typically observed at high winter polar latitudes. Once these stratospheric ices are formed, they will diffuse throughout Titan’s lower atmosphere and most will eventually precipitate to the surface, where they are expected to contribute to Titan’s regolith. Early and important contributions were first made by the InfraRed Interferometer Spectrometer (IRIS) on Voyager 1, followed by notable contributions from IRIS’ successor, the Cassini Composite InfraRed Spectrometer (CIRS), and to a lesser extent, from Cassini’s Visible and Infrared Mapping Spectrometer (VIMS) and the Imaging Science Subsystem (ISS) instruments. All three remote sensing instruments made new ice cloud discoveries, combined with monitoring the seasonal behaviors and time evolution throughout Cassini’s 13-year mission tenure. A significant advance by CIRS was the realization that co-condensing chemical compounds can account for many of the CIRS-observed stratospheric ice cloud spectral features, especially for some that were previously puzzling, even though some of the observed spectral features are still not well understood. Relevant laboratory transmission spectroscopy efforts began just after the Voyager encounters, and have accelerated in the last few years due to new experimental efforts aimed at simulating co-condensed ices in Titan’s stratosphere. This review details the current state of knowledge regarding the organic ice clouds in Titan’s stratosphere, with perspectives from both observational and experimental standpoints.

Astronomy↗
NASA NTRS2018

Organic Ices in Titan's Stratosphere

Titan’s stratospheric ice clouds are by far the most complex of any observed in the solar system, with over a dozen organic vapors condensing out to form a suite of pure and co-condensed ices, typically observed at high winter polar latitudes. Once these stratospheric ices are formed, they will diffuse throughout Titan’s lower atmosphere and most will eventually precipitate to the surface, where they are expected to contribute to Titan’s regolith. Early and important contributions were first made by the InfraRed Interferometer Spectrometer (IRIS) on Voyager 1, followed by notable contributions from IRIS’ successor, the Cassini Composite InfraRed Spectrometer (CIRS), and to a lesser extent, from Cassini’s Visible and Infrared Mapping Spectrometer (VIMS) and the Imaging Science Subsystem (ISS) instruments. All three remote sensing instruments made new ice cloud discoveries, combined with monitoring the seasonal behaviors and time evolution throughout Cassini’s 13-year mission tenure. A significant advance by CIRS was the realization that co-condensing chemical compounds can account for many of the CIRS-observed stratospheric ice cloud spectral features, especially for some that were previously puzzling, even though some of the observed spectral features are still not well understood. Relevant laboratory transmission spectroscopy efforts began just after the Voyager encounters, and have accelerated in the last few years due to new experimental efforts aimed at simulating co-condensed ices in Titan’s stratosphere. This review details the current state of knowledge regarding the organic ice clouds in Titan’s stratosphere, with perspectives from both observational and experimental standpoints.

C. M. Anderson↗
NASA NTRS2018

Organic Ices in Titan’s Stratosphere

Titan’s stratospheric ice clouds are by far the most complex of any observed in the solar system, with over a dozen organic vapors condensing out to form a suite of pure and co-condensed ices, typically observed at high winter polar latitudes. Once these stratospheric ices are formed, they will diffuse throughout Titan’s lower atmosphere and most will eventually precipitate to the surface, where they are expected to contribute to Titan’s regolith. Early and important contributions were first made by the InfraRed Interferometer Spectrometer (IRIS) on Voyager 1, followed by notable contributions from IRIS’ successor, the Cassini Composite InfraRed Spectrometer (CIRS), and to a lesser extent, from Cassini’s Visible and Infrared Mapping Spectrometer (VIMS) and the Imaging Science Subsystem (ISS) instruments. All three remote sensing instruments made new ice cloud discoveries, combined with monitoring the seasonal behaviors and time evolution throughout Cassini’s 13-year mission tenure. A significant advance by CIRS was the realization that co-condensing chemical compounds can account for many of the CIRS-observed stratospheric ice cloud spectral features, especially for some that were previously puzzling, even though some of the observed spectral features are still not well understood. Relevant laboratory transmission spectroscopy efforts began just after the Voyager encounters, and have accelerated in the last few years due to new experimental efforts aimed at simulating co-condensed ices in Titan’s stratosphere. This review details the current state of knowledge regarding the organic ice clouds in Titan’s stratosphere, with perspectives from both an observational and experimental standpoint.

Ices↗
NASA NTRS2014

Advancing Technologies for Climate Observation

Climate research needs Accurate global cloud ice measurements Cloud ice properties are fundamental controlling variables of radiative transfer and precipitation Cost-effective, sensitive instruments for diurnal and wide-swath coverage Mature technology for space remote sensing IceCube objectivesDevelop and validate a flight-qualified 883 GHz receiver for future use in ice cloud radiometer missions Raise TRL (57) of 883 GHz receiver technology Reduce instrument cost and risk by developing path to space for COTS sub-mm-wave receiver systems Enable remote sensing of global cloud ice with advanced technologies and techniques

radiative transfer↗
NASA NTRS2019

IceCube: Spaceflight Demonstration of 883-GHz Cloud Radiometer for Future Science

Cloud ice play important roles in Earth’s climate and weather systems through their interactions with atmospheric radiation, dynamics, energy and precipitation processes. Submillimeter (submm) wave remote sensing at 200-1000 GHz is able to provide the sensitivity not covered by visible (VIS)/infrared (IR) and low-frequency microwave (MW) sensors (10-183 GHz), and measure cloud ice in the middle-to-upper troposphere. The IceCube 883-GHz cloud radiometer is the latest of NASA’s efforts to advance the technology readiness level (TRL) of submm-wave receiver technology for future compact, low-cost implementation of Earth observing systems. Emerging CubeSat opportunities allow a fast-track development and spaceflight demonstration of IceCube on a 3-U CubeSat. Funded by NASA’s In-Space Validation of Earth Science Technologies (InVEST) program and Science Mission Directorate (SMD), IceCube is the first CubeSat developed and flown by Goddard Space Flight Center (GSFC) in 2.5 years, using commercial off-the-shelf (COTS) components and subsystems. It was successfully released from International Space Station (ISS) in May 2017, acquired 15-month science data and produced the first global map of the 883-GHz cloud ice. It achieved all mission objectives and provided a pathway for future cost-effective cloud observations from CubeSat constellation.

Submm-wave remote sensing↗
NASA NTRS2004

On the Retrieval of Ice Cloud Particle Shapes from POLDER Measurements

Shapes of ice crystals can significantly affect the radiative transfer in ice clouds. The angular distribution of the polarized reflectance over ice clouds strongly depends on ice crystal shapes. Although the angular-distribution features of the total or polarized reflectance over ice clouds implies a possibility of retrieving ice cloud particle shapes by use of remote sensing data, the accuracy of the retrieval must be evaluated. In this study, a technique, which applies single ice crystal habit and multidirectional polarized radiance to retrieve ice cloud particle shapes, is assessed. Our sensitivity studies show that the retrieved particle shapes &om this algorithm can be considered good approximations to those in actual clouds in calculation of the phase matrix elements. Although a fractal poly-crystal shape or an inhomogeneous hexagonal column may also produce this type of phase functions, more representative single-scattering properties from combinations of natural particle shapes and size distributions may still be necessary in accurate retrieval of other cloud properties such as optical thickness and particle size.

Sun, W.↗
NASA NTRS2020

Cloud Detection over Snow and Ice with Oxygen A- and B-band Observations from the Earth Polychromatic Imaging Camera (EPIC)

Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and cold/bright surfaces; cloud mask algorithms often heavily rely on shortwave infrared (IR) channels over such surfaces. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) does not have infrared channels, which makes cloud detection over snow and ice surfaces even more challenging. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios in the A band (764, 780 nm) and B band (688, 680 nm) for cloud detection over the snow and ice surfaces. We develop a novel elevation and zenith-angle-dependent threshold scheme based on radiative transfer model simulations that achieves significant improvements over the existing algorithm. When compared against a composite cloud mask based on geosynchronous Earth orbit (GEO) and low Earth orbit (LEO) sensors, the positive detection rate over snow and ice surfaces increased from around 36 % to 65 % while the false detection rate dropped from 50 % to 10 % for observations of January 2016 and 2017. The improvement in July is less substantial due to relatively better performance in the current algorithm. The new algorithm is applicable for all snow and ice surfaces including Antarctic, sea ice, high-latitude snow, and high-altitude glacier regions. This method is less reliable when clouds are optically thin or below 3 km because the sensitivity is low in oxygen band ratios for these cases.

EPIC↗
NASA NTRS2011

Fog and Cloud Induced Aerosol Modification Observed by AERONET

Large fine mode (sub-micron radius) dominated aerosols in size distributions retrieved from AERONET have been observed after fog or low-altitude cloud dissipation events. These column-integrated size distributions have been obtained at several sites in many regions of the world, typically after evaporation of low altitude cloud such as stratocumulus or fog. Retrievals with cloud processed aerosol are sometimes bimodal in the accumulation mode with the larger size mode often approx.0.4 - 0.5 microns radius (volume distribution); the smaller mode typically approx.0.12 to aprrox.0.20 microns may be interstitial aerosol that were not modified by incorporation in droplets and/or aerosol that are less hygroscopic in nature. Bimodal accumulation mode size distributions have often been observed from in situ measurements of aerosols that have interacted with clouds, and AERONET size distribution retrievals made after dissipation of cloud or fog are in good agreement with particle sizes measured by in situ techniques for cloud-processed aerosols. Aerosols of this type and large size range (in lower concentrations) may also be formed by cloud processing in partly cloudy conditions and may contribute to the shoulder of larger size particles in the accumulation mode retrievals, especially in regions where sulfate and other soluble aerosol are a significant component of the total aerosol composition. Observed trends of increasing aerosol optical depth (AOD) as fine mode radius increased suggests higher AOD in the near cloud environment and therefore greater aerosol direct radiative forcing than typically obtained from remote sensing, due to bias towards sampling at low cloud fraction.

Eck, T. F.↗
NASA NTRSDate not supplied

Ice-Over-Water Cloud Properties in an Artificial Neural Network Approach

Clouds are a crucial component of the atmospheric energy system, particularly the radiative balance within, above, and below the troposphere. The vertical distribution of cloud mass and phase determines layer heating rates, the loss of radiation to space, and the amount of radiative heating at the surface. Thus, it is important to know how clouds are distributed both vertically and horizontally at all times of day. Satellite remote sensing is the only approach available to monitor clouds day and night around the globe. In this paper several artificial neural network (ANN) algorithms, employing several Aqua MODIS infrared channels, profiles of relative humidity and temperature from GMAO numerical weather analyses, and the retrieved total cloud visible optical depth, are trained to detect multilayer ice-over-water cloud systems and to retrieve some of their properties as identified by a year of 2008 Aqua MODIS data matched with CloudSat and CALIPSO (CC) cloud profiles. The CC lidar and radar profiles provide the vertical structure that serves as output truth for the multilayer algorithm. The neural networks were trained using one year (2008) of cloud top height data from the CC dataset, with correlation around 0.94 (0.95) and MAE as low as 0.82 (0.81) km for nonpolar regions during the day (night). Applying the trained ANN to independent year 2009 MODIS data resulted in a combined ML and single layer hit rate of 86.4% (85.1%) for nonpolar regions during the day (night). Since the ANN is trained using near-nadir MODIS pixels, infrared radiance corrections were developed as a function of view zenith angle from MODIS and applied to off-nadir pixels when processing MODIS swath data. The multilayer amount derived with the ANN is relatively invariant with increasing view zenith angle compared to the multilayer amount without the corrections.

MODIS↗
NASA NTRS1990

Analysis of ER-2 radiometer and lidar observations from the 1987 marine stratus experiment

Extensive remote sensing observations of marine stratus clouds were acquired from the NASA ER-2 aircraft during the 1987 FIRE stratus field experiment. The observations included high spatial resolution imaging radiometry at eighteen wavelengths and active lidar cloud top profiling. Analysis of these data can provide results to both enhance and extend aircraft in-situ cloud physics observations. For the spectral imaging radiometry observations of the marine stratus, a potentially useful result was obtained. For near infrared wavelengths, a large number of the bidirectional reflectance observations included persistent and significant single scattering features. With few exceptions, the features were not correspondingly observed at visible wavelengths. An initial comparison to direct cloud physics measurements give a good agreement (Spinhirne and Nakajima, 1989). The analysis of lidar returns from marine stratus cloud tops were shown to be potentially valuable for study of the microphysical and dynamic characteristics of the clouds (Boers et al., 1988, Spinhirne et al., 1989). Analysis involving cloud top water content and height spectra was applied to some of the extensive lidar observations of the 1987 field experiment. Derivation of cloud top radiative parameters and comparison to in-situ observations are planned.

Spinhirne, James D.↗
NASA NTRS1993

Scientific goals of the Cooperative Multiscale Experiment (CME)

Mesoscale Convective Systems (MCS) form the focus of CME. Recent developments in global climate models, the urgent need to improve the representation of the physics of convection, radiation, the boundary layer, and orography, and the surge of interest in coupling hydrologic, chemistry, and atmospheric models of various scales, have emphasized the need for a broad interdisciplinary and multi-scale approach to understanding and predicting MCS's and their interactions with processes at other scales. The role of mesoscale systems in the large-scale atmospheric circulation, the representation of organized convection and other mesoscale flux sources in terms of bulk properties, and the mutually consistent treatment of water vapor, clouds, radiation, and precipitation, are all key scientific issues concerning which CME will seek to increase understanding. The manner in which convective, mesoscale, and larger scale processes interact to produce and organize MCS's, the moisture cycling properties of MCS's, and the use of coupled cloud/mesoscale models to better understand these processes, are also major objectives of CME. Particular emphasis will be placed on the multi-scale role of MCS's in the hydrological cycle and in the production and transport of chemical trace constituents. The scientific goals of the CME consist of the following: understand how the large and small scales of motion influence the location, structure, intensity, and life cycles of MCS's; understand processes and conditions that determine the relative roles of balanced (slow manifold) and unbalanced (fast manifold) circulations in the dynamics of MCS's throughout their life cycles; assess the predictability of MCS's and improve the quantitative forecasting of precipitation and severe weather events; quantify the upscale feedback of MCS's to the large-scale environment and determine interrelationships between MCS occurrence and variations in the large-scale flow and surface forcing; provide a data base for initialization and verification of coupled regional, mesoscale/hydrologic, mesoscale/chemistry, and prototype mesoscale/cloud-resolving models for prediction of severe weather, ceilings, and visibility; provide a data base for initialization and validation of cloud-resolving models, and for assisting in the fabrication, calibration, and testing of cloud and MCS parameterization schemes; and provide a data base for validation of four dimensional data assimilation schemes and algorithms for retrieving cloud and state parameters from remote sensing instrumentation.

Cotton, William↗
NASA NTRS1995

Analysis of measurements for solid state laser remote lidar system

The merits of using lidar systems for remote measurements of various atmospheric processes such as wind, turbulence, moisture, and aerosol concentration are widely recognized. Although the lidar technology has progressed considerably over the past two decades, significant research particularly in the area of solid state lidars remains to be conducted in order to fully exploit this technology. The work performed by the UAH (University of Alabama in Huntsville) personnel under this Delivery Order concentrated on analyses of measurements required in support of solid state laser remote sensing lidar systems which are to be designed, deployed, and used to measure atmospheric processes and constituents. UAH personnel has studied and recommended to NASA/MSFC the requirements of the optical systems needed to characterize the detection devices suitable for solid state wavelengths and to evaluate various heterodyne detection schemes. The 2-micron solid state laser technology was investigated and several preliminary laser designs were developed and their performance for remote sensing of atmospheric winds and clouds from a spaceborne platform were specified. In addition to the laser source and the detector, the other critical technologies necessary for global wind measurements by a spaceborne solid state coherent lidar systems were identified to be developed and demonstrated. As part of this work, an analysis was performed to determine the atmospheric wind velocity estimation accuracy using the line-of-sight measurements of a scanning coherent lidar. Under this delivery order, a computer database of materials related to the theory, development, testing, and operation of lidar systems was developed to serve as a source of information for lidar research and development.

Amzajerdian, Farzin↗