Earth Reflectivity Research Articles

Topological Signature of Stratospheric Poincaré-Gravity Waves

Abstract The rotation of Earth breaks time-reversal and reflection symmetries in an opposite sense north and south of the equator, leading to a topological origin for certain atmospheric and oceanic equatorial waves. Away from the equator, the rotating shallow-water and stably stratified primitive equations exhibit Poincaré inertia–gravity waves that have nontrivial topology as evidenced by their strict superinertial time scale and a phase singularity in frequency–wavevector space. This nontrivial topology then predicts, via the principle of bulk-interface correspondence, the existence of two equatorial waves along the equatorial interface, the Kelvin and Yanai waves. To directly test the nontrivial topology of Poincaré-gravity waves in observations, we examine ERA5 data and study cross correlations between the wind velocity and geopotential height of the midlatitude stratosphere at the 50 hPa height. We find the predicted vortex and antivortex in the relative phase of the geopotential height and velocity at the high frequencies of the waves. By contrast, lower-frequency planetary waves are found to have trivial topology also as expected from theory. These results demonstrate a new way to understand stratospheric waves and provide a new qualitative tool to investigate waves in other components of the climate system.

Response of propagation of ELF electromagnetic waves through the morning ionosphere to small density variations caused by infrasonic wave

We consider the problem of the effect of small plasma density variations on the propagation and reflection of ELF (extremely-low-frequency) electromagnetic wave incident on the morning ionosphere from above. Modifications of the electromagnetic wave field near the Earth surface and coefficient of wave energy reflection from ionosphere caused by infrasonic wave are studied. The greatest modifications of the field on the Earth surface and reflection coefficient are related to the density perturbations at altitudes of strong electromagnetic wave attenuation (80–110 km). Reflection of electromagnetic waves is especially sensitive to the plasma density perturbations if the value of horizontal refractive index is close to a unit. In this case, modulation percentage of reflection coefficient can exceed the modulation percentage of density in the infrasonic wave by an order of magnitude. The parametric influence of plasma density perturbations in an infrasonic wave on the ELF electromagnetic field is analyzed. If the values of the horizontal wave numbers of the electromagnetic and infrasonic waves are close to each other, the field of the electromagnetic wave near the Earth surface can increase several times. The obtained results are important for understanding the interconnection of ionospheric wave processes of different nature. The study of the modulation of coefficient of ELF reflection from the ionosphere is relevant for explaining the operation modes of a plasma magnetospheric maser.

A geometry-dependent surface Lambertian-equivalent reflectivity product for UV–Vis retrievals – Part 1: Evaluation over land surfaces using measurements from OMI at 466 nm

Abstract. The anisotropy of the Earth's surface reflection has implications for satellite-based retrieval algorithms that utilize climatological surface reflectivity databases that do not depend upon the observation geometry. This is the case for most of the current ultraviolet and visible (UV–Vis) cloud, aerosol, and trace-gas algorithms. The illumination–observation dependence of surface reflection is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF effect, we use the concept of geometry-dependent surface Lambertian-equivalent reflectivity (GLER), which is derived from the top-of-atmosphere (TOA) radiance computed with Rayleigh scattering and surface BRDF for the exact geometry of a satellite-based pixel. We present details on the implementation of land and water surface BRDF models, and we evaluate our GLER product over land surfaces using observed Sun-normalized radiances at 466 nm. The input surface BRDF parameters for computing TOA radiance are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations. The observed TOA radiance for comparison is from the Ozone Monitoring Instrument (OMI). The comparison shows good agreement between observed and calculated OMI reflectivity in 2006 in typical geographical regions, with correlation coefficients greater than 0.8 for some regions. Seasonal variations of clear-sky OMI reflectivity (i.e., with minimum clouds and aerosols) closely follow those computed using MODIS-derived GLER over land. GLER also captures the cross-track dependence of OMI-derived LER, though the latter is slightly higher than the former presumably owing to residual cloud and aerosol (nonabsorbing) contamination, particularly over dark surfaces (heavily vegetated regions such as mixed forest, croplands, and grasslands). Calibration differences between OMI and MODIS may also be responsible for some of this bias. The standard OMI climatological surface reflectivity database predicts higher radiances than GLER and OMI observations with different seasonal variation over most regions and does not have any angular-dependent variation. Overall, our evaluation demonstrates that the GLER product adequately accounts for surface BRDF effects while at the same time simplifying the surface BRDF implementation within the existing OMI retrieval infrastructure; use of our GLER product requires changes only to the input surface reflectivity database.

Broadband Least-Squares Wave-Equation Migration

We introduce an effective iterative Least-Squares Wave-Equation Migration (LS-WEM) solution for broadband imaging. Least-Squares Migration (LSM) solutions are designed to produce images of the subsurface corrected for wavefield distortions caused by acquisition and propagation effects. They implicitly solve for the earth reflectivity by means of data residual reduction in an iterative fashion, which usually demands intensive computation. The LS-WEM is implemented using a visco-acoustic anisotropic one-way wave-equation wavefield propagator that is able to fully utilize both the broader seismic bandwidth and the high-resolution velocity information from Full Waveform Inversion (FWI). Our implementation combines the one-way extrapolator with fast linear inversion solvers into an efficient migration inversion system. Application to the 2D Sigsbee2b synthetic model improves the sub-salt illumination by balancing the image amplitudes and reducing the effects of the shadow zones, enhances temporal resolution by broadening the frequency spectrum, balances the wavenumber content and improves images of faults and dipping salt flanks. In addition, LS-WEM converges rapidly to the true solution, reducing the data residuals by 90% in only four iterations. Application to real 3D datasets from the Gulf of Mexico and the North Sea demonstrates high-resolution imaging with reduced acquisition footprint effects, improved spatial frequency content, and better structural imaging at all depths.

Shallow water acoustic techniques to investigate transitional environments: A case study over Boka Kotorska Bay

The eastern border of the Adriatic Sea shows several examples of transitional areas marked by fragmented coastlines, islands and coastal bays. Bays and estuaries interact with the main basin influencing it and being influenced by it in terms of circulation patterns and freshwater supply. Coastal and transitional areas represent highly dynamic, rapidly changing environments subjected to multiple interactions with the marine-land-fluvial systems related processes. Processes such as coastal erosion, seawater intrusion, pollution and sediment transport and deposition affect these areas. One of the most important transitional areas along the entire Adriatic coast, from both an environmental and a socio-economic viewpoint, is the bay of Boka Kotorska, where the sea enters inland for over 20 km. The Bay is located along the Montenegro margin and is part of a ria coastal system surrounded by high mountains part of the Dinaric range. Boka Kotorska Bay includes three major basins, connected by two narrow straits with a maximum depth of 67 m. Despite its historical and geostrategic role the morphology and geology of the Bay is poorly known. Coastal areas are among the most urbanized and populated regions; for these reasons the application of geophysical minimally invasive methods are required in order to collect geological and morphological data. High resolution seismic reflection techniques such as CHIRP systems, adopting a non-impulsive source wavelet, are ideal to carry out seismic surveys in transitional environments. Here, we present a detailed description of this system in order to furnish the mathematical basis for forward modelling. Moreover, we outline a procedure to estimate the earth reflectivity by inversion of the recorded signal envelope (reflection strength), i.e., the standard way to store CHIRP data. Reflection strength data alone, characterizing the signal power as a function of time, do not retain all the characteristics of the recorded signal they represent and thus, cannot be further processed and hardly be compared with results from forward modeling. New high resolution multibeam and seismic reflection data collected in the Boka Kotorska Bay reveal unknown details of present-day morphologies and sedimentary infilling geometries. Several processes are involved in shaping the bay and its seafloor. Our results show that the observed morphologies are due to the interaction at different timescales of climate, water circulation, sealevel changes, erosion, sedimentation and tectonics constrained by the geological and structural setting of the area.

The need of an ethics of planetary sustainability

AbstractThe concept of sustainability is widely acknowledged as a political guideline. Economic, ecological, social and cultural aspects of sustainability are already under discussion. Current space mining efforts demand that the discussion become a broader one about ‘planetary sustainability’, including the space surrounding Earth. To date, planetary sustainability has mainly been used with reference to Earth only and I will extend it here, elaborating on a similar NASA initiative. This article (1) sketches the contemporary economic–political initiatives which call for a special reflection of Earth's location in space, and then (2) discusses the meaning of the concept of sustainability in this context. Next, (3) I relate the discussion to the issue of planetary and environmental protection, before, (4) finally, presenting a philosophical and theological perspective that seems particularly able to broach the issue of the multiple dimensions of sustainability in this context. This is the concept of constructive-critical realism. My overview of the topic concludes with (5) a summarizing outlook.

Least-squares full-wavefield migration

We present a least-squares solution for depth migration of the full reflected wavefield. The algorithm combines primary and high-order reflected energy and significantly enhances the image illumination and resolution compared to those of conventional migration. Least-squares full-wavefield migration (LS-FWM) directly computes the earth's reflectivity, thereby avoiding crosstalk noise often observed in imaging using high-order reflections. Iteratively solving an inversion problem is computationally intensive and can suffer from instability issues; however, we develop an efficient least-squares procedure by combining a fast and accurate one-way wave-equation propagator with an effective linear inversion solver. An advanced regularization method is also employed to stabilize the inversion by controlling the over-fitting problem. Successful applications to both synthetic and field data examples demonstrate that LS-FWM greatly improves the imaging illumination and resolution compared to conventional migration.

Influence of aerosols, clouds, and sunglint on polarization spectra of Earthshine

Ground-based observations of the Earthshine, i.e., the light scattered by Earth to the Moon, and then reflected back to Earth, simulate space observations of our planet and represent a powerful benchmark for the studies of Earth-like planets. Earthshine spectra are strongly linearly polarized, owing to scattering by molecules and small particles in the atmosphere of the Earth and surface reflection, and may allow us to measure global atmospheric and surface properties of planet Earth. Aims. We aim to interpret already published spectropolarimetric observations of the Earthshine by comparing them with new radiative transfer model simulations including a fully realistic three-dimensional (3D) surface-atmosphere model for planet Earth. We used the highly advanced Monte Carlo radiative transfer model MYSTIC to simulate polarized radiative transfer in the atmosphere of the Earth without approximations regarding the geometry, taking into account the polarization from surface reflection and multiple scattering by molecules, aerosol particles, cloud droplets, and ice crystals. We have shown that Earth spectropolarimetry is highly sensitive to all these input parameters, and we have presented simulations of a fully realistic Earth atmosphere-surface model including 3D cloud fields and two-dimensional (2D) surface property maps. Our modeling results show that scattering in high ice water clouds and reflection from the ocean surface are crucial to explain the continuum polarization at longer wavelengths as has been reported in Earthshine observations taken at the Very Large Telescope in 2011 (3.8 % and 6.6 % at 800 nm, depending on which part of Earth was visible from the Moon at the time of the observations). We found that the relatively high degree of polarization of 6.6 % can be attributed to light reflected by the ocean surface in the sunglint region.

Back to basics on broadband seismic amplitudes, phase and resolution

Marine broadband seismic results typically have observed amplitude spectra that are inconsistent with the earth reflectivity spectra measured from spatially coincident well data. The most notable inconsistency is a visual bias towards stronger ultra-low frequency amplitudes in the 0–10 Hz range on seismic data. Whilst useful in principle for more accurate elastic seismic inversion with less dependence upon low frequency model (LFM) building and for more stable full waveform inversion (FWI), the low frequency bias will degrade seismic resolution if not balanced properly during processing. Furthermore, the observed seismic amplitude spectra on pre-stack data vary with increasing offset and the phase can strongly vary in a frequency-dependent manner. These variations are attributed to three first-order processes: 1. Progressive attenuation of higher frequencies with longer travel paths, 2. NMO stretch, and 3. Offset-dependent tuning, and may easily be compounded by inappropriate parameterization of various processing and imaging steps. A key component of elastic seismic inversion is the extraction and scaling of several angle-dependent and depth-dependent wavelets. These wavelets are ideally independent of the aforementioned processes but inevitably they are not, and the angle ranges used in the inversion impact the significance of NMO stretch and offset-dependent tuning. Even if these various considerations can all be accommodated during processing, the resolution of seismic images is limited by the resolution of the velocity model, the scattering assumptions of the imaging algorithms used, and the a priori information used to constrain imaging and inversion. After reviewing the principles of seismic wavefield propagation in the contemporary context of broadband seismic methods, largely pursued with the ambition of removing sea surface-related ghost effects, I discuss the additional uncertainties introduced into seismic signal processing by broader bandwidth data — notably at the low frequency end. I consider two rather different ‘broadband seismic’ perspectives: 1. The industry must progress towards higher fidelity and resource-consuming measurements of every source event and every receiver measurement in order to effectively deconvolve the ‘system response’ from the data, or, 2. High-end imaging solutions can automatically eliminate the ‘source term’ without requiring detailed source information — assuming that wavefield separation has robustly accounted for dynamic variations in receiver geometry. A longer term consideration of imaging suggests that the classical sequential processing paradigm is in fact dead, that the definition of ‘noise’ is changing, and that advances in hardware are enabling solutions to long-standing challenges with cross-talk artifacts and irregular illumination. The addition of appropriate a priori information into joint migration and inversion allows historical assumptions about the unknown velocity model having a smooth background to be dismissed, and step changes in velocity model resolution may be achievable. I conclude by discussing how higher resolution velocity models will translate to less non-physical efforts in processing that can corrupt pre-stack amplitude, pre-stack phase and (elastic) image resolution.

A fast automatic multichannel blind seismic inversion for high-resolution impedance recovery

The inversion of seismic reflection data for acoustic impedance (AI) is a common and accepted method for the interpretation of poststack seismic data. The original mathematical problem is nonlinear due to the nonlinearity of relation between the AI and the earth reflectivity series and also the insufficiency of information about the source wavelet. Furthermore, the problem is ill posed due to the lack of low and high frequencies in the data. We have developed a multichannel blind inversion and solved it for obtaining the AI model and the wavelet directly from seismic reflection data. We found a solution to the overall problem by alternating between two subproblems, corresponding to the AI and wavelet recovery. Having an estimation of the wavelet, the algorithm directly inverts multichannel data for a high-resolution AI model, having blocky structures in the sense of total variation (TV) regularization, while satisfying a priori low-frequency information. The advantages of the split Bregman technique and the discrete cosine transform are used to build a fast and efficient algorithm for solving the nonlinear impedance inversion with TV regularization. Having an estimate of the AI model, the wavelet is updated by restricting it to have a sparse representation in a wavelet transformation domain while predicting the observed data. Numerical tests using simulated 2D data obtained from the benchmark Marmousi model and also 2D field data confirm that the proposed algorithm stably generates accurate estimates of complex AI models and complicated wavelets, simultaneously.

Tutorial: Wavelet estimation for well ties

Wavelets are filters that keep us from seeing what we set out to see in seismic data: the earth's reflectivity. Through deconvolution, we try to remove the wavelet from the data. In tying wells, we make a wavelet interact with well-log measurements to create a synthetic representation of the seismic according to the borehole.

Feasibility of approximate broadband estimation of acoustic impedance profile from first principles and band-limited reflection data

Because seismic reflection data are band limited, acoustic impedance profiles derived from them are nonunique. The conventional inversion methods counter the nonuniqueness either by stabilizing the answer with respect to an initial model or by imposing mathematical constraints such as sparsity of the reflection coefficients. By making a nominal assumption of an earth model locally consisting of a stack of homogeneous and horizontal layers, we have formulated a set of linear equations in which the reflection coefficients are the unknowns and the recursively integrated seismic trace constitute the data. Drawing only on first principles, the Zoeppritz equation in this case, the approach makes a frontal assault on the problem of reconstructing reflection coefficients from band-limited data. The local layer-cake assumption and the strategy of seeking a singular value decomposition solution of the linear equations counter the nonuniqueness, provided that the objective is to reconstruct a smooth version of the impedance profile that includes only its crude structures. Tests on synthetic data generated from elementary models and from measured logs of acoustic impedance demonstrated the efficacy of the method, even when a significant amount of noise was added to the data. The emergence of consistent estimates of impedance, approximating the original impedance, from synthetic data generated for several frequency bands has inspired our confidence in the method. The other attractive outputs of the method are as follows: (1) an accurate estimate of the impedance mean, (2) an accurate reconstruction of the direct-current (DC) frequency of the reflectivity, and (3) an acceptable reconstruction of the broad outline of the original impedance profile. These outputs can serve as constraints for either more refined inversions or geologic interpretations. Beginning from the restriction of band-limited data, we have devised a method that neither requires a starting input model nor imposes mathematical constraints on the earth reflectivity and still yielded significant and relevant geologic information.

Nonlinear multichannel impedance inversion by total-variation regularization

The analysis of acoustic impedance (AI) allows for the mapping of seismic reflection data to lithology, and hence it plays an important role in the interpretation of poststack seismic data. The AI is obtainable from the inversion of the earth reflectivity series. Efficient deconvolution methods have been developed for recovering the reflectivity series from band-limited poststack data, which are multiple free, zero offset, and migrated. However, calculation of the AI from the reflectivity, when considering the spatial correlation of the impedance parameters, demands the solution of a constrained nonlinear inverse problem. Two efficient algorithms are proposed for solving the nonlinear impedance problem in multichannel form with the total-variation (TV) constraint to recover impedance maps with blocky structures. The first uses the continuous earth model for reflectivity, which allows linearizing the problem in the logarithm domain. The second uses the discrete (layered) earth model for reflectivity. In this case, a nonlinear problem is solved in the original domain. The main properties of the algorithms, which are built based on the split-Bregman technique and the discrete cosine transform are as follows: (1) They are multichannel inversion procedures, so they respect the spatial and temporal correlation of the data, (2) they impose the TV constraint on the parameters to generate blocky structures, (3) they are fast such that a large 3D impedance model with a blocky structure can be recovered easily on a personal computer, and (4) the computational complexities of both algorithms are the same. Numerical tests using simulated 2D data obtained from a benchmark Marmousi model and also 2D and 3D field data confirmed that the proposed algorithm generates more accurate with higher resolution impedance models compared with the conventional methods.

Understanding climate change: science, policy, and practice

1. Climate Change in the Public Sphere 1.1. Communicating about climate change 1.2. The state of the science 1.3. Responding to climate change: mitigation and adaptation 1.4. The state of the policy 1.4.1. The United Nations Framework Convention on Climate Change and the Kyoto Protocol 1.4.2. The United Nations Conference on Environment and Development (Rio, and Rio +20) 1.4.3. The Intergovernmental Panel on Climate Change 1.5. The scale of the challenge: accelerating action on climate change 1.6. Roadmap to the book 2. Basic System Dynamics 2.1. What's a system? 2.1.1. System parts and interactions 2.1.2. Stocks and flows 2.1.3. Feedbacks 2.1.4. Lags 2.1.5. Function or purpose 2.2. Earth's Climate System: The parts and interconnections 2.2.1. Atmosphere, Hydrosphere, Biosphere, Geosphere, and Anthroposphere 2.2.2. The Ins and Out of Earth's Energy Budget 3. Climate controls: Energy from the Sun 3.1. Incoming Solar Radiation 3.1.1. Blackbody radiation: the Sun versus Earth 3.1.2. Our place in space: the Goldilocks planet 3.2. Natural Variability 3.2.1. 4.5 billion years of solar energy 3.2.2. Orbital controls: baseline variability in the past million years 3.2.3. Sunspots: how big a deal? 3.3. Mitigation strategies and policy tools 4. Climate Controls: Earth's Reflectivity 4.1. Natural Variability 4.1.1. At Earth's surface: Ice, water, and vegetation 4.1.2. In the atmosphere: Aerosols and clouds 4.2. Anthropogenic Variability 4.2.1. Land-use changes 4.2.2. Anthropogenic Aerosols 4.3. Mitigation strategies and policy tools 5. Climate Controls: The Greenhouse effect 5.1. How does the greenhouse effect work? 5.1.1. Characteristics of a good greenhouse gas 5.1.2. Energy flows in a greenhouse world 5.2. The unperturbed carbon cycle and natural greenhouse variability 5.2.1. Carbon stocks and flows 5.2.2. Timescales of natural greenhouse variability 5.2.3. Feedbacks involving the greenhouse effect 5.3. Anthropogenic interference 5.3.1. Perturbed stocks, flows, and chemical fingerprints 5.3.2. Cumulative carbon emissions: a budget 6. The Core of Climate Change Mitigation: Reducing Greenhouse Gas Emissions and Transforming the Energy System 6.1. Introduction to reducing greenhouse gas emissions 6.2. The Global Energy System 6.3. Mitigation Strategies 6.3.1. Demand-side mitigation: energy efficiency and conservation 6.3.2. Supply-side mitigation 6.3.3. Carbon capture and storage 6.4. Fostering accelerated and transformative mitigation 7. Climate Models 7.1. Climate Model Basics 7.1.1. Physical Principles 7.1.2. The Role of Observations 7.1.3. Time and Space 7.1.4. Parameterization 7.1.5. Testing climate models 7.2. Types of climate models 7.2.1. Energy Balance Models 7.2.2. Earth System Models of Intermediate Complexity 7.2.3. General Circulation Models 7.2.4. Regional Climate Models 7.2.5. Integrated Assessment Models 7.3. Certainties and Uncertainties 8. Future Climate: Emissions, climate, and what we do about it 8.1. Emissions scenarios SRES scenario 'families' and storylines 8.1.1. Post-SRES and Representative Concentration Pathways 8.1.2. 8.2. Global Climate in 2100 Temperature, precipitation, sea level rise, and extreme events 8.2.1. Uncertainty 8.2.2. 8.3. Regional forecasting 8.4. Backcasting 8.5. Scale of the challenge: Transforming emissions pathways 9. Climate Change Impacts on Natural Systems 9.1. Observed Impacts Impacts on Land 9.1.1. Impacts in the Oceans 9.1.2. 9.2. Adaptation in Natural Systems 9.3. Policy Tools and Progress International tools 9.3.1. National and sub-national tools 9.3.2. 9.4. Conclusions 10. Climate Change Impacts on Human Systems 10.1. Introduction 10.2. Key concepts in climate change impacts and adaptation 10.3. Observed and Projected Impacts 10.3.1. Climate change impacts on food and water 10.3.2. Climate change impacts on cities and infrastructure 10.3.3. Equity implications: Health, culture, and global distribution of wealth 10.4. Adaptation in human systems 10.5. Policy Tools and Progress 10.5.1. Policy tools for adaptation 10.5.2. International and national adaptation 10.5.3. Sub-national adaptation 10.5.4. Social movements and human behavior change: the root of the adaptation conundrum 11. The Frontier: Innovative Action on Climate Change 11.1. Integrating Adaptation and Mitigation: Pursuing Sustainability 11.2. What Road will we choose? The ethics of geoengineering 11.3. Transformative change: reorienting development paths to yield a sustainable future 11.4. Conclusions and future directions

Detection limits of albedo changes induced by climate engineering

Geoengineering the climate by increasing the Earth's reflectivity has been suggested. In this Perspective, the detectability of various methods is investigated. Although satellite observations can detect large changes in albedo, smaller increases caused by some methods of geoengineering are indistinguishable from natural variability. This raises the question of how such schemes would be managed if their impacts can not be quantified.

Measurement of the earthshine polarization in theB, V, R, andIbands as function of phase

The characterization of the polarimetric properties of the planet Earth is important for the interpretation of expected observations and the planning of future instruments. We present a multi-wavelengths and multi-phase set of benchmark values for the polarization signal of the integrated light from the planet Earth derived from new polarimetric observations of the earthshine back-scattered from the Moon's dark side. Using a new, specially designed wide field polarimeter we measured the fractional polarization of the earthshine in the B, V, R and I filters for Earth phase angles alpha between 30{\deg} and 110{\deg}. The phase dependence of the earthshine polarization is fitted by a function p x sin(alpha)^2. To determine the polarization of the planet Earth we correct our earthshine measurements by a polarization efficiency function for the lunar surface derived from measurements of lunar samples from the literature. The polarization of the earthshine decreases towards longer wavelengths and is about a factor 1.3 lower for the higher albedo highlands. For mare regions the measured maximum polarization is about 13 % at quadrature in the B band. The resulting fractional polarizations for Earth are 24.6 % for the B band, 19.1 % for the V band, 13.5 % for the R band, and 8.3 % for the I band. Together with literature values for the spectral reflectivity of Earth we obtain a contrast between the polarized flux of the Earth and the (total) flux of the Sun with an uncertainty of less than 20 % and we find that the best phase to detect an Earth twin is around an Earth phase alpha=65{\deg}. The polarimetric models of Earth-like planets from Stam (2008) are in qualitative agreement with our results but there are also significant differences which might guide more detailed computations.

Earth Albedo perturbations on Low Earth Orbit Cubesats

This work investigates the orbital perturbations of the cubesats that lie on LEO due to Earth albedo. The motivation for this paper originated in the investigation of the orbital perturbations for closed- Earth pico-satellites due to the sunlight reflected by the Earth (the albedo). Having assumed that the Sun lies on the equator, the albedo irradiance is calculated using a numerical model in which irradiance depends on the geographical latitude, longitude and altitude of the satellite. However, in the present work the longitude dependency is disregarded. Albedo force and acceleration components are formulated using a detailed model in a geocentric equatorial system in which the Earth is an oblate spheroid. Lagrange planetary equations in its Gaussian form are used to analyze the orbital changes when <TEX>$e{\neq}0$</TEX> and <TEX>$i{\neq}0$</TEX>. Based on the Earth's reflectivity data measured by NASA Total Ozone Mapping Spectrometer (TOMS project), the orbital perturbations are calculated for some cubesats. The outcome of the numerical test shows that the albedo force has a significant contribution on the orbital perturbations of the pico-satellite which can affect the satellite life time.

전력선 유도 환경에서의 지면 반사계 영향 분석

전력선에 의한 전자유도 환경에서 가장 보편적 영향 요인이라 할 수 있는 대지의 유도전압 감쇠 효과에 대하여 분석하였다. 전력선은 원통좌표계의 라인소스로 표현되고 계의 분석은 베셀함수와 웨이브 트랜스포메이션에 의한 이의 변형 적용을 통하여 해석된다. 라인소스로부터 방사된 전자계는 지표면에서 반사되어 관측점의 피유도원 매체에 합성되는데 이것의 영향을 알기 위하여 본 논문에서는 베셀함수에 의한 지면 반사계수를 직접 구하여 산출하도록 적용하였다. 본 논문에서 설계된 통상의 유도 환경의 배치 관계에 따르면 지면반사에 의한 원천 유도원 전압과의 합성 효율은 유도전압을 감쇠시키는 차폐효과로서 60～70%정도의 범위를 나타내었다.

Optimal Beamforming for Range-Doppler Ambiguity Minimization in Squinted SAR

A method is proposed to optimize the radiation pattern of a planar array in order to maximize the signal-to-ambiguity-ratio for a squinted synthetic aperture radar (SAR) observation geometry. The optimal beamformer is the generalized eigenvector associated with a pair of matrices that depends on observation geometry and the Earth reflectivity model. The proposed approach is valid for any array configuration. This enables adaptivity to surface background and T/R module failures, thus increasing system robustness.

Quantitative regularity analysis of offset-vector sampling for seismic acquisition geometry

Symmetric acquisition geometry consisting of identical sampling of shots and receivers, can maintain the spatial continuity of the wavefield automatically, according to symmetric sampling theory. However, asymmetric geometry is often adopted in practical seismic exploration applications. Such geometry can cause uneven sampling and is necessary to be assessed for its sampling performance prior to acquisition. In conventional survey design, based on the common mid-point (CMP) analysis for a horizontally layered earth or common reflection point (CRP) analysis for a complex subsurface structure, the quality of acquisition geometry is generally judged by such bin properties as effective fold, offset scalar and azimuth distributions. However, these conventional approaches are limited by an incomplete understanding of the offset-vector sampling. Therefore, we propose a new method for quantitatively evaluating the continuity of offset-vector sampling including four spatial coordinates of shot and receiver. On the basis of physical potential energy and force-balance principle, it analyzes the regularity coefficient of offset-vector sampling as a whole using potential function model and takes into account fold, offset-scalar and azimuth distribution factors. The combination of regularity coefficients of every bin can produce spatial continuity distribution of offset-vector sampling. Similar to symmetric sampling, this approach emphasize the spatial relationships between adjacent bins rather than single bin attribute, since it aims to maintain the spatial continuity of the wavefield which allows the faithful reconstruction of the underlying continuous wavefield. Using this method, we can quantitatively compare spatial continuity distribution for different seismic acquisition geometries, and then choose the better acquisition scheme.