Spaceborne laser filamentation for atmospheric remote sensing

A proof‐of‐concept of space‐borne laser filamentation for atmospheric remote sensing is presented. The remote generation of laser filaments from an Earth‐orbiting satellite is shown by numerical simulations to be theoretically possible for a large range of laser parameters. The model includes a realistic representation of the stratified atmosphere and accounts for multi‐species ionization and the dependence of air density upon the molecule type and altitude profile. The remote generation of a white light continuum extending from 350 nm to 1.1 μm within the filament is demonstrated, and hereby proposed as an atmospheric in‐situ light source for monitoring greenhouse gases and pollutants on a global scale by light detection and ranging (lidar) techniques. Scaling laws are also derived for estimating the filament altitude as a function of peak pulse power (3 GW‐3 TW), beam radii (10‐200 cm) and for three different curvatures (300, 390, 500 km) for femtosecond infrared (800 nm) pulses. We find that operating conditions for remote supercontinuum generation are already available with current ground‐based mobile laser technology and within reach of future space laser systems.

     

Iterative regularization methods for atmospheric remote sensing

In this paper we present different inversion algorithms for nonlinear ill-posed problems arising in atmosphere remote sensing. The proposed methods are Landweber's method (LwM), the iteratively regularized Gauss-Newton method, and the conventional and regularizing Levenberg-Marquardt method. In addition, some accelerated LwMs and a technique for smoothing the Levenberg-Marquardt solution are proposed. The numerical performance of the methods is studied by means of simulations. Results are presented for an inverse problem in atmospheric remote sensing, i.e., temperature sounding with an airborne uplooking high-resolution far-infrared spectrometer.     

Relationship between different approaches to derive weighting functions related to atmospheric remote sensing problems

The paper is devoted to the investigation of the relationship between different methods used to derive weighting functions required to solve numerous inverse problems related to the remote sensing of the Earth's atmosphere by means of scattered solar light observations. The first method commonly referred to as the forward-adjoint approach is based on a joint solution of the forward and adjoint radiative transfer equations and the second one requires the linearized forward radiative transfer equation to be solved. In the framework of the forward-adjoint method we consider two approaches commonly used to derive the weighting functions. These approaches are referenced as the “response function” and the “formal solution” techniques, respectively. We demonstrate here that the weighting functions derived employing the formal solution technique can also be obtained substituting the analytical representations for the direct forward and direct adjoint intensities into corresponding expressions obtained in the framework of the response function technique. The advantages and disadvantages of different techniques are discussed.     

大气痕量气体遥感探测仪发展现状和趋势

阐述了大气痕量气体探测技术的发展历程;详细介绍了几种国外先进的大气痕量气体遥感探测仪器的设计理念、工作原理和功能、工作模式、谱段设置和主要技术指标。讨论了我国遥感用星载大气痕量气体探测仪器的发展现状,给出了两种典型探测仪器的工作模式、谱段设置和主要性能指标。指出了未来星载大气痕量气体探测仪器的发展方向是提高遥感仪器的光谱分辨率、空间分辨率、灵敏度和定标精度以及发展主动遥感技术等,意在为我国今后这一领域的发展提供借鉴。     

O2A-band line parameters to support atmospheric remote sensing

Numerous satellite and ground-based remote sensing measurements rely on the ability to calculate O₂A-band [b¹Σ_g⁺←X³Σ_g⁻(0,0)] spectra from line parameters, with combined relative uncertainties below 0.5% required for the most demanding applications. In this work, we combine new ¹⁶O₂A-band R-branch measurements with our previous P-branch observations, both of which are based upon frequency-stabilized cavity ring-down spectroscopy. The combined set of data spans angular momentum quantum number, J′ up to 46. For these measurements, we quantify a J-dependent quadratic deviation from a standard model of the rotational distribution of the line intensities. We provide calculated transition wave numbers, and intensities for J′ up to 60. The calculated line intensities are derived from a weighted fit of the generalized model to an ensemble of data and agree with our measured values to within 0.1% on average, with a relative standard deviation of ≈0.3%. We identify an error in the calculated frequency dependence of the O₂A-band line intensities in existing spectroscopic databases. Other reported lineshape parameters include a revised set of ground-state energies, self- and air-pressure-broadening coefficients and self- and air-Dicke-narrowing coefficients. We also report a band-integrated intensity at 296 K of 2.231(7)×10⁻²² cm molec⁻¹ and Einstein-A coefficient of 0.0869(3) s⁻¹.     

An efficient inversion algorithm for atmospheric remote sensing with application to UV limb observations

In this paper we present a retrieval algorithm for atmospheric remote sensing. The algorithm combines Tikhonov regularization and the iteratively regularized Gauss-Newton method and is devoted to the solution of multi-parameter inverse problems with simple bounds on the variables. The basic features of the algorithm: the solution of the bound-constrained minimization problem, the selection of the optimal regularization parameter, the derivation of the global regularization matrix and the characterization of the solution (error analysis) are discussed in detailed. The inversion algorithm is applied to ozone retrieval from SCIAMACHY limb scatter measurements in the ultraviolet spectral range.     

Information operator approach and iterative regularization methods for atmospheric remote sensing

In this study, we present the main features of the information operator approach for solving linear inverse problems arising in atmospheric remote sensing. This method is superior to the stochastic version of the Tikhonov regularization (or the optimal estimation method) due to its capability to filter out the noise-dominated components of the solution generated by an inappropriate choice of the regularization parameter. We extend this approach to iterative methods for nonlinear ill-posed problems and derive the truncated versions of the Gauss-Newton and Levenberg-Marquardt methods. Although the paper mostly focuses on discussing the mathematical details of the inverse method, retrieval results have been provided, which exemplify the performances of the methods. These results correspond to the NO₂ retrieval from SCIAMACHY limb scatter measurements and have been obtained by using the retrieval processors developed at the German Aerospace Center Oberpfaffenhofen and Institute of Environmental Physics of the University of Bremen.     

Mean temperature in a closed basin by remote sensing

Summary In this paper a procedure to determine the mean vertical temperature in a closed shallow basin will be presented. The procedure is based on the remotely observed surface temperature implemented by a calibration point at which usual meteorological measurements are performed. By the energy conservation equation applied at the calibration point the behaviour of the mean vertical temperature is obtained. Field measurement have been performed (June 1987) in a basin called Comacchio Valley (Italia). Experimental results are shown. This work has been in part supported by the Consiglio Nazionale delle Ricerche, Italy. The VAX 11/750 of the Centro Interdipartimentale di Calcolo Automatico ed Informatica Applica (CICAIA) of the University of Modena, Italy, has been used.     

Decoupling error for the atmospheric correction in ocean color remote sensing algorithms

This paper studies the decoupling error associated with the atmospheric correction procedures in the ocean color remote sensing algorithms. The decoupling error is caused by the lack of proper consideration of multiple scattering between the atmospheric and ocean components. In other words, the atmosphere and ocean are not coupled properly. A vector radiative transfer model for the coupled atmosphere and ocean (CAO) system based on the successive order of scattering (SOS) method is used to study the error. The inherent optical properties (IOPs) of the ocean are provided by the most updated bio-optical models. Two wavelengths are used in the study, 412 and 555 nm. For a detector located just above the ocean interface, the decoupling errors range from 0.3% to 7% at 412 nm; and from 0.3% to 3 % at 555 nm for zenith viewing angles smaller than 70°. The decoupling errors are significantly larger for larger zenith viewing angles for this detector. For a detector at the top of the atmosphere (TOA), it is hard to separate the decoupling error from the error introduced by the diffuse transmittance. If we assume the upwelling radiance is uniform just below the ocean surface when estimating the diffuse transmittance, the decoupling errors are from ?4% to 8% for zenith viewing angles smaller than 70°; and negative decoupling errors show up at mainly large zenith viewing angles.     

Spectral line finding program for atmospheric remote sensing using full radiation transfer

We have developed a line-by-line code to simulate atmospheric spectra in the infrared spectral region assuming a remote light source of selectable temperature. Selecting the source temperature allows simulation of, for example, solar absorption spectra, lunar absorption spectra or emission spectra. The code is applicable for different geometries, from the ground, balloon or from satellite, and allows a simple search for the most suitable lines for the retrieval of atmospheric trace gas concentrations for the different geometries. In addition, a first estimate of the optimized microwindow size and the most important interfering gases that need to be considered is calculated automatically. This approach is of importance in cases where it is necessary to analyze numerous lines simultaneously to get sufficient precision in the trace gas concentration retrievals. Examples for H₂O and CO are given.     

A new k-interval selection technique for fast atmospheric radiance calculation in remote sensing applications

A new technique is proposed to generate the k-interval parameters, including the number of k-intervals, the equivalent absorption coefficients, and the quadrature weights when using the correlated k-distribution method for the computation of spectrally integrated three-dimensional (3D) atmospheric radiance. The main difference between the proposed technique and the traditional exponential sum fitting technique is that only quadrature weights are involved in the optimization process. To avoid the ill-conditioned problem in the proposed technique, the absorption coefficients with high value are dealt with by the delta log(k) (Δlog(k)) technique instead of involving them in the fitting procedure. The performance of the proposed technique is illustrated by radiance calculation results of cloudless and cloudy atmosphere for three different band settings. Results show that there are less relative errors with the proposed optimization technique than with the Δlog(k) technique under the same number of k-intervals. However, as the absorption becomes stronger, the performance of the proposed technique gradually decreases to the Δlog(k) technique. The relative root-mean-square error (RMSE) of radiance for 3D cloudy atmosphere can be controlled in less than 2% when the number of k-intervals is less than 10 particularly for weak absorption band, the RMSEs are less than 1% with only 6 terms.     

Improvements for ground-based remote sensing of atmospheric aerosol properties by additional polarimetric measurements

We discuss the improvements in the aerosol properties characterization resulting from the additional multi-wavelength polarization measurements measured by a new CIMEL polarized sun/sky-photometer, CE318-DP. In order to process direct-sun, sky and polarization measurements in a wide spectral range (340–1640 nm), we developed new calibration methods and strategies, e.g. using the Langley plot method to calibrate both direct-sun irradiance and sky radiance, as well as combining laboratory facilities with a vicarious method to calibrate the polarized sky measurements. For studying the impact of new polarimetric measurements on the retrievals of aerosol properties, we have processed an extensive record of field measurements using an updated Dubovik and King retrieval algorithm [Dubovik O, Sinyuk A, Lapyonok T, Holben BN, Mishchenko MI, et al. Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust. J Geophys Res 2006;111:D11208.]. A preliminary analysis shows that adding polarization in the inversion can reduce possible errors (notably for about 30% of our field cases) in the fine mode size distribution, real part of refractive index and particle shape parameter retrievals, especially for small particles.     

Modeling of atmospheric radiative transfer with polarization and its application to the remote sensing of tropospheric ozone

Light reflected or transmitted by a planetary atmosphere contains information about particles and molecules in the atmosphere. Therefore, accurate modeling of the radiation field may be used to retrieve information on atmospheric composition. In this paper, a multi-layer model for a vertically inhomogeneous atmosphere is implemented by using the doubling-adding method for a plane-parallel atmosphere. By studying the degree of linear polarization of the transmitted and reflected solar light in the Huggins bands, we find significant differences between tropospheric ozone and stratospheric ozone. The effects of tropospheric ozone change on the linear polarization are 10 times more than that of the same amount of stratospheric ozone change. We also show the aerosol effect on the linear polarization, but this effect is wavelength independent as compared to that caused by the tropospheric ozone change. The results provide a theoretical basis for the retrieval of tropospheric ozone from measurement of linear polarization of the scattered sunlight both from the ground and from a satellite.     

偏振在多角度遥感中的太阳耀光消除的应用

在进行水色遥感时,水面的镜面反射产生的太阳耀光,影响水体信息的提取和利用。以前的研究表明,当入射角为水体的布儒斯特角时,偏振可以消除太阳耀光,但是这种方法条件过于苛刻,现实中很难实现。针对这种情况,推导了自然光入射到水面后其反射光的偏振状态以及光线入射角与水体偏振度的关系。理论上证明了以非布儒斯特角入射时偏振消除太阳耀光的可能性,计算了从各个角度入射到纯净水体表面太阳耀光剥离的程度,实验验证了结论。     

An efficient analytical approach for calculating line mixing in atmospheric remote sensing applications

Collisional coupling between energy states in a molecule undergoing an optical transition can alter the line shape associated with the transition, an effect known as line mixing. Accounting for this effect in the analysis of remote sensing measurements of Earth's atmosphere by the Atmospheric Chemistry Experiment (ACE) yields reduced residuals, which leads to improved performance in the volume mixing ratio retrievals for some molecules. Analytical expressions are presented for the imaginary components of the polynomial ratios from the Humlicek algorithm, which provides approximate solutions to the complex probability function. These imaginary components are employed in the calculation of line mixing using the Rosenkranz first order approximation. Examples of line mixing in ACE measurements are presented, including a set of CH₄ lines that exhibit both line mixing and speed dependence. An efficient, analytical approach is proposed for calculating line shapes with a combination of line mixing and speed dependence. FORTRAN routines for calculating line mixing effects are provided as a supplement to the paper.     

Passive remote sensing of planetary atmospheres and retrievals of atmospheric macro- and microphysical parameters

In two recent papers, referred to as Paper 1 and Paper 2 in the main text, we have pursued an idea that atmospheric weighting functions for any geophysical parameters essentially consist of two kinds of entities: weighting functions for the atmospheric radiative parameters, which directly enter the radiative transfer equation, and partial derivatives of the atmospheric radiative parameters with respect to atmospheric geophysical parameters. Corresponding analysis was performed for non-scattering and scattering planetary atmospheres for nadir-viewing geometry and thermal spectral region. In the present paper we conduct a study of the second group of above entities, the partial derivatives of atmospheric radiative parameters with respect to atmospheric geophysical parameters. Along the way, we analyze the role of radiative parameters of individual atmospheric constituents, which serve as intermediaries between the total radiative parameters of the atmosphere and its geophysical parameters. The obtained expressions, combined with radiative weighting functions, are used in the end-to-end expressions for the weighting functions obtained for various specific geophysical parameters.     

O2A-band line parameters to support atmospheric remote sensing. Part II: The rare isotopologues

Frequency-stabilized cavity ring-down spectroscopy (FS-CRDS) was employed to measure over 100 transitions in the R-branch of the (0,0) band for the rare O₂ isotopologues. The use of ¹⁷O- and ¹⁸O-enriched mixtures allowed for line positions to be measured for the ¹⁶O¹⁷O, ¹⁶O¹⁸O, ¹⁷O₂, ¹⁷O¹⁸O, and ¹⁸O₂ isotopologues. Simultaneous fits to the upper and lower states were performed for each isotopologue using the FS-CRDS positions supplemented by microwave, millimeter, submillimeter, terahertz, and Raman ground state positions from the literature. Positions, line intensities, pressure broadening parameters, and collisional narrowing parameters are reported for the ¹⁶O¹⁸O and ¹⁶O¹⁷O isotopologues which are based upon the present study and our earlier FS-CRDS work (Long et al. J Quant Spectrosc Radiat Transfer 2010;111:2021 [18] and Robichaud et al. J Phys Chem A 2009;113:13089 [15]). The calculated line intensities include a term for the observed Herman-Wallis-like interaction and correct a frequency-dependent error, which is present in current spectroscopic databases.     

On the accuracy of covariance matrix: Hessian versus Gauss-Newton methods in atmospheric remote sensing with infrared spectroscopy

Most retrieval schemes use a linear approximation of the radiative transfer function within each iteration as well as for error analysis. Like most standard methods, the improved Hessian method relies on a quadratic form of the cost function and linear approximation in the error analysis. Often, there is no robust criterion in determining step size that can be used to calculate covariance matrix by discrete perturbation of the cost function in the Hessian approach. The Hessian method improved recently, however, overcomes this problem by employing adaptive algorithm which uses small step sizes in steep directions and large step sizes in flat directions of the cost function. The results of retrievals of atmospheric trace gases from simulated limb emission spectra show that Gauss-Newton algorithm and the improved Hessian generally give nearly identical volume mixing ratios and error covariance matrices in the original state vector space. Due to interlevel correlations, however, the agreement in the uncertainities in the original state vector coordinate system is partly lost in a space in which the elements of state vector are independent after orthogonal coordinate transformation. The significant discrepancies between the estimated uncertainities by the two methods are found to be related with elements of state vector that are dominantly controlled by flattest eigenvector directions of the inverse covariance matrix. The improved Hessian method determines the uncertainities in those shallowest directions with better accuracy than Gauss-Newton approach. The performance of the Hessian method is also found to be better in resolving structures related to the shallowest eigenvector directions as revealed by better vertical resolutions in the retrieved profiles of the trace species.