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At least 199 records · Page 11

Satellite Optical Remote Sensing of Clouds and Aerosols: From Particle Single-Scattering and Gaseous Absorption Through Radiative Transfer to Retrieval Products

Clouds and aerosols are fundamental regulators of Earth’s radiation budget and climate system, influencing both solar and terrestrial radiation through scattering, absorption, and emission processes. Accurate characterization of their physical and radiative properties from space requires a rigorous understanding of particle single-scattering, gaseous absorption, and radiative transfer in the atmosphere, as well as reliable inversion methods. This review synthesizes the physical foundations and algorithmic implementations of satellite-based passive optical remote sensing of clouds and aerosols, spanning the ultraviolet to thermal infrared spectral range. Beginning with electromagnetic scattering theory and state-of-the-art methods for computing single-scattering by nonspherical particles and computationally efficient methods for accounting for atmospheric absorption, we discuss the radiative transfer framework underpinning cloud and aerosol retrievals. The connection between single-scattering and multiple-scattering is rigorously formulated. We then summarize operational and research-grade retrieval techniques, including cloud masking and thermodynamic phase determination, CO₂ slicing for cloud-top pressure, the Nakajima-King shortwave bi-spectral, and infrared split-window approaches for cloud optical thickness and effective particle size, inversion algorithms for determining aerosol properties from multi-spectral and/or multi-angle radiometric and polarimetric measurements, and active-passive sensing synergy. Examples of the global cloud and aerosol climatologies are illustrated using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR). Furthermore, the unique strengths of active remote sensing techniques based on spaceborne lidar observations are briefly elaborated in the context of studying ice clouds composed of randomly and horizontally oriented ice crystals, which is a significant challenge for conventional passive remote sensing techniques. By connecting physical theory to practical retrievals, this review highlights both the maturity of current methodologies and the remaining challenges in reducing uncertainties in particle morphology, vertical structure, absorption, and aerosol-cloud interactions. Furthermore, the impact of artificial intelligence (AI) on atmospheric remote sensing is briefly addressed.

Aerosols↗

On the Ability of Space- Based Passive and Active Remote Sensing Observations of CO2 to Detect Flux Perturbations to the Carbon Cycle

Space-borne observations of CO2 are vital to gaining understanding of the carbon cycle in regions of the world that are difficult to measure directly, such as the tropical terrestrial biosphere, the high northern and southern latitudes, and in developing nations such as China. Measurements from passive instruments such as GOSAT (Greenhouse Gases Observing Satellite) and OCO-2 (Orbiting Carbon Observatory 2), however, are constrained by solar zenith angle limitations as well as sensitivity to the presence of clouds and aerosols. Active measurements such as those in development for the Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS) mission show strong potential for making measurements in the high-latitude winter and in cloudy regions. In this work we examine the enhanced flux constraint provided by the improved coverage from an active measurement such as ASCENDS. The simulation studies presented here show that with sufficient precision, ASCENDS will detect permafrost thaw and fossil fuel emissions shifts at annual and seasonal time scales, even in the presence of transport errors, representativeness errors, and biogenic flux errors. While OCO-2 can detect some of these perturbations at the annual scale, the seasonal sampling provided by ASCENDS provides the stronger constraint. Plain Language Summary: Active and passive remote sensors show the potential to provide unprecedented information on the carbon cycle. With the all-season sampling, active remote sensors are more capable of constraining high-latitude emissions. The reduced sensitivity to cloud and aerosol also makes active sensors more capable of providing information in cloudy and polluted scenes with sufficient accuracy. These experiments account for errors that are fundamental to the top-down approach for constraining emissions, and even including these sources of error, we show that satellite remote sensors are critical for understanding the carbon cycle.

tropical terrestrial biosphere↗

3D Cloud Tomography and Droplet Size Retrieval from Multi-Angle Polarimetric Imaging of Scattered Sunlight from Above

Tomography aims to recover a three-dimensional (3D) density map of a medium or an object. In medical imaging,it is extensively used for diagnostics via X-ray computed tomography (CT). We define and derive a tomographyof cloud droplet distributions via passive remote sensing. We use multi-view polarimetric images to fit a 3Dpolarized radiative transfer (RT) forward model. Our motivation is 3D volumetric probing of vertically-developedconvectively-driven clouds that are ill-served by current methods in operational passive remote sensing. Currenttechniques are indeed based on strictly 1D RT modeling and applied to a single cloudy pixel, where cloud geometrydefaults to that of a plane-parallel slab. Incident unpolarized sunlight, once scattered by cloud droplets, changesits polarization state according to droplet size. Therefore, polarimetric measurements in the rainbow and gloryangular regions can be used to infer the droplet size distribution. This work defines and derives a framework for afull 3D tomography of cloud droplets for both their mass concentration in space and their distribution across arange of sizes. This gridded 3D retrieval of key microphysical properties is made tractable by our novel approachthat involves a restructuring and partial linearization of an open-source polarized 3D RT code to accommodate aspecial two-step iterative optimization technique. Physically-realistic synthetic clouds are used to demonstrate themethodology with rigorous uncertainty quantification, while a real-world cloud imaged by AirMSPI is processedto illustrate the new remote sensing capability

Schechner, Yoav Y.↗

Development of the Synthetic Aperture Radiometer ESTAR and the Next Generation

ESTAR is a research instrument built to develop the technology of aperture synthesis for passive remote sensing of Earth from space. Aperture synthesis is an interferometric technology that addresses the problem of putting large antenna apertures in space to achieve the spatial resolution needed for remote sensing at long wavelengths ESTAR was a first step (synthesis only across track and only at horizontal polarization). The development has progressed to a new generation instrument that is dual polarized and does aperture synthesis in two dimensions. Among the plans for the future is technology to combine active and passive remote sensing.

LeVine, David M.↗

optical Instruments for Remote Sensing from Space

This review covers the optical design of passive remote sensing optical instruments. The review concentrates on the design of spaceborne multispectral cameras and imaging spectometers. The major designs that have been produced over the past ten years are discussed, and new designs for future imaging spectrometers are presented.

Optical Instruments Remote Sensing↗

A History of NASA Remote Sensing Contributions to Archaeology

During its long history of developing and deploying remote sensing instruments, NASA has provided a scientific data that have benefitted a variety of scientific applications among them archaeology. Multispectral and hyperspectral instrument mounted on orbiting and suborbital platforms have provided new and important information for the discovery, delineation and analysis of archaeological sites worldwide. Since the early 1970s, several of the ten NASA centers have collaborated with archaeologists to refine and validate the use of active and passive remote sensing for archeological use. The Stennis Space Center (SSC), located in Mississippi USA has been the NASA leader in archeological research. Together with colleagues from Goddard Space Flight Center (GSFC), Marshall Space Flight Center (MSFC), and the Jet Propulsion Laboratory (JPL), SSC scientists have provided the archaeological community with useful images and sophisticated processing that have pushed the technological frontiers of archaeological research and applications. Successful projects include identifying prehistoric roads in Chaco canyon, identifying sites from the Lewis and Clark Corps of Discovery exploration and assessing prehistoric settlement patterns in southeast Louisiana. The Scientific Data Purchase (SDP) stimulated commercial companies to collect archaeological data. At present, NASA formally solicits "space archaeology" proposals through its Earth Science Directorate and continues to assist archaeologists and cultural resource managers in doing their work more efficiently and effectively. This paper focuses on passive remote sensing and does not consider the significant contributions made by NASA active sensors. Hyperspectral data offers new opportunities for future archeological discoveries.

Giardino, Marco J.↗

NASA's Future Earth Science Missions for Global Observations

NASA is at fore-front in developing active and passive remote sensing technologies and unique capabilities towards space-based observations for understanding the complexities and interactions among Earth system components. The world is facing significant environmental challenges and a robust, integrated, and flexible system of observations and models are needed for understanding the short-and long term impact on the Earth system. A fundamental challenge for the coming decade is to ensure that space-based observations, analyses, better interpretive understanding, enhanced predictive models, broadened international community participation, and improved means for information assimilation and disseminations are well coordinated to realize the full economic, societal, and security benefit of Earth science. This presentation will provide an overview of enabling active and passive remote sensing technologies and techniques, NASA's future vision for Earth science missions for global observations, and the challenges associated in applying them for societal benefit.

Upendra N Singh↗

Structural Health Monitoring Sensor Development at NASA Langley Research Center

NASA is applying considerable effort on the development of sensor technology for structural health monitoring (SHM). This research is targeted toward increasing the safety and reliability of aerospace vehicles, while reducing operating and maintenance costs. Research programs are focused on applications to both aircraft and space vehicles. Sensor technologies under development span a wide range including fiber-optic sensing, active and passive acoustic sensors, electromagnetic sensors, wireless sensing systems, MEMS, and nanosensors. Because of their numerous advantages for aerospace applications, fiber-optic sensors are one of the leading candidates and are the major focus of this presentation. In addition, recent advances in active and passive acoustic sensing will also be discussed.

Prosser, W. H.↗

Validation of the Cloud_CCI (Cloud Climate Change Initiative) cloud products in the Arctic

The role of clouds in the Arctic radiation budget is not well understood. Ground-based and airborne measurements provide valuable data to test and improve our understanding. However, the ground-based measurements are intrinsically sparse, and the airborne observations are snapshots in time and space. Passive remote sensing measurements from satellite sensors offer high spatial coverage and an evolving time series, having lengths potentially of decades. However, detecting clouds by passive satellite remote sensing sensors is challenging over the Arctic because of the brightness of snow and ice in the ultraviolet and visible spectral regions and because of the small brightness temperature contrast to the surface. Consequently, the quality of the resulting cloud data products needs to be assessed quantitatively. In this study, we validate the cloud data products retrieved from the Advanced Very High Resolution Radiometer (AVHRR) post meridiem (PM) data from the polar-orbiting NOAA-19 satellite and compare them with those derived from the ground-based instruments during the sunlit months. The AVHRR cloud data products by the European Space Agency (ESA) Cloud Climate Change Initiative (Cloud_CCI) project uses the observations in the visible and IR bands to determine cloud properties. The ground-based measurements from four high-latitude sites have been selected for this investigation: Hyytiälä (61.84°N, 24.29°E), North Slope of Alaska (NSA; 71.32°N, 156.61°W), Ny-Ålesund (Ny-Å; 78.92°N, 11.93°E), and Summit (72.59°N, 38.42°W). The liquid water path (LWP) ground-based data are retrieved from microwave radiometers, while the cloud top height (CTH) has been determined from the integrated lidar–radar measurements. The quality of the satellite products, cloud mask and cloud optical depth (COD), has been assessed using data from NSA, whereas LWP and CTH have been investigated over Hyytiälä, NSA, Ny-Å, and Summit.

54 ENVIRONMENTAL SCIENCES↗

Radar scene generation for tactical decision aids

The Mueller matrix and polarization covariance matrix for polarimetric radar systems was studied. The clutter is modeled by a layer of random permittivity, described by a three-dimensional correlation function, with variance, and horizontal and vertical correlation lengths. A general mixing formula was derived for discrete scatters immersed in a host medium. The results are applicable to general multiphase mixtures. The strong fluctuation theory was used to derive the backscattering cross sections, and was further extended to include higher order co-polarized and cross-polarized moments. A two-layer anisotropic random medium model was developed for the active and passive remote sensing of ice fields. A three-layer random medium model was adopted to study the volume scattering effects for the active and passive microwave remote sensing of snow-covered ice fields. The snow layer was simulated by an isotropic random medium and the ice layer by an anisotropic random medium. The vegetation canopy and snow-covered ice field were studied with a three-layer model, an isotropic random medium layer overlying an anisotropic random medium. The dyadic Green's function of the three-layer medium and the scattered electromagnetic intensities with Born approximation were calculated.

Kong, J. A.↗

A mathematical characterization of vegetation effect on microwave remote sensing from the Earth

In passive microwave remote sensing of the earth, a theoretical model that utilizes the radiative transfer equations was developed to account for the volume scattering effects of the vegetation canopy. Vegetation canopies such as alfalfa, sorghum, and corn are simulated by a layer of ellipsoidal scatterers and cylindrical structures. The ellipsoidal scatterers represent the leaves of vegetation and are randomly positioned and oriented. The orientation of ellipsoids is characterized by a probability density function of Eulerian angles of rotation. The cylindrical structures represent the stalks of vegetation and their radii are assumed to be much smaller than their lengths. The underlying soil is represented by a half-space medium with a homogeneous permittivity and uniform temperature profile. The radiative transfer quations are solved by a numerical method using a Gaussian quadrature formula to compute both the vertical and horizontal polarized brightness temperature as a function of observation angle. The theory was applied to the interpretation of experimental data obtained from sorghum covered fields near College Station, Texas.

Choe, Y.↗

IRIS - A concept for microwave sensing of soil moisture and ocean salinity

A concept is described for passive microwave sensing of soil moisture and ocean salinity from space. The Inflatable Radiometric Imaging System (IRIS) makes use of a large-diameter, offset-fed, parabolic-torus antenna with multiple feeds, in a conical pushbroom configuration.

soil moisture ocean salinity parabolic-torus anten↗

Investigation of remote sensing techniques of measuring soil moisture

Major activities described include development and evaluation of theoretical models that describe both active and passive microwave sensing of soil moisture, the evaluation of these models for their applicability, the execution of a controlled field experiment during which passive microwave measurements were acquired to validate these models, and evaluation of previously acquired aircraft microwave measurements. The development of a root zone soil water and soil temperature profile model and the calibration and evaluation of gamma ray attenuation probes for measuring soil moisture profiles are considered. The analysis of spatial variability of soil information as related to remote sensing is discussed as well as the implementation of an instrumented field site for acquisition of soil moisture and meteorologic information for use in validating the soil water profile and soil temperature profile models.

Newton, R. W.↗