Search Results (16)

A fast and accurate radiative transfer model is the prerequisite in the field of atmospheric remote sensing for limb atmospheric inversion to tackle the drawback of slow calculation speed of traditional atmospheric radiative transfer models. This paper established a fast computing model (ANN-HASFCM) for high-spectral-resolution absorption spectra by using artificial neural networks and PCA (principal component analysis) spectral reconstruction technology. This paper chose the line-by-line radiative transfer model (LBLRTM) as the comparative model and simulated training spectral data in the oxygen A-band (12,900–13,200 cm⁻¹). Subsequently, ANN-HASFCM was applied to the retrieval of the atmospheric density profile with the data of the Global Ozone Monitoring by an Occultation of Stars (GOMOS) instrument. The results show that the relative error between the optical depth spectra calculated by LBLRTM and ANN-HASFCM is within 0.03–0.65%. In the process of using the global-fitting algorithm to invert GOMOS-measured atmospheric samples, the inversion results using Fast-LBLRTM and ANN-HASFCM as forward models are consistent, and the retrieval speed of ANN-HASFCM is more than 200 times faster than that of Fast-LBLRTM (reduced from 226.7 s to 0.834 s). The analysis shows the brilliant application prospects of ANN-HASFCM in limb remote sensing. Full article

Aerosol research is important for the protection of the ecological environment, the improvement of air quality, and as a response to climate change. In this study, a random forest (RF) estimation model of aerosol optical depth (AOD) and extinction coefficient vertical profiles was, respectively, established using Orbiting Carbon Observatory-2 (OCO-2) oxygen-A band (O₂ A-band) data from China and its surrounding areas in 2016, combined with geographical information (longitude, latitude, and elevation) and viewing angle data. To address the high number of OCO-2 O₂ A-band channels, principal component analysis (PCA) was employed for dimensionality reduction. The model was then applied to estimate the aerosol extinction coefficients for the region in 2017, and its validity was verified by comparing the estimated values with the Cloud-Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) Level 2 extinction coefficients. In the comprehensive analysis of overall performance, an AOD model was initially constructed using variables, achieving a correlation coefficient (R) of 0.676. Subsequently, predictions for aerosol extinction coefficients were generated, revealing a satisfactory agreement between the predicted and the actual values in the vertical direction, with an R of 0.535 and a root mean square error (RMSE) of 0.107 km⁻¹. Of the four seasons of the year, the model performs best in autumn (R = 0.557), while its performance was relatively lower in summer (R = 0.442). Height had a significant effect on the model, with both R and RMSE decreasing as height increased. Furthermore, the accuracy of aerosol profile inversion shows a dependence on AOD, with a better accuracy when AOD is less than 0.3 and RMSE can be less than 0.06 km⁻¹. Full article

The stellar occultation technique is capable of atmospheric trace gas detection using the molecule absorption characteristics of the stellar spectra. In this paper, the non-iterative and iterative retrieval methods for oxygen and air density detection by stellar occultation are investigated. For the single-band average transmission data in the oxygen 761 nm A-band, an onion-peeling algorithm is used to calculate the effective optical depth of each atmospheric layer, and then the optical depth is used to retrieve the oxygen number density. The iteration method introduces atmospheric hydrostatic equilibrium and the ideal gas equation of state, and it achieves a more accurate retrieval of the air density under the condition of a priori temperature deviation. Finally, this paper analyzes the double solution problem in the iteration process and the ideas to improve the problem. This paper provides a theoretical basis for the development of a new type of atmospheric density detection method. Full article

In recent decades, there has been an increasing interest in making use of satellite measurements for identifying trends in atmospheric composition and climate. Instruments like GOME-2 and TROPOMI are dedicated to air-quality and global trace gas monitoring. For the accurate retrieval of columnar information of the trace gases, cloud correction is necessary. This work is meant to examine the quality of the GOME-2 operational cloud product from AC SAF and to propose enhancements of the current dataset to improve the retrieval of the NO₂ and HCHO tropospheric gases. Full article

Stellar occultation instruments detect the transmission of stellar spectra through the planetary atmosphere to retrieve densities of various atmospheric components. This paper introduces an idea of using instruments with bandpass filters for stellar occultation detection. According to the characteristics of the occultation technique for oxygen density measurement, a full-link forward model is established, and the average transmission under a typical nocturnal atmosphere is calculated with the help of the HITRAN database, occultation simulation and a 3D ray-tracing program. The central wavelength and bandwidth suitable for 760 nm oxygen A-band absorption measurement are discussed. This paper also compares the results of the forward model with GOMOS spectrometer data under this band, calculates the observation signal-to-noise ratio corresponding to different instrument parameters, and target star magnitudes. The results of this paper provide a theoretical basis for the development of a stellar occultation technique with a bandpass filter and guidance on the instrument design. Full article

Measurements of the global cloud vertical structure (CVS) are critical to better understanding the effects of the CVS on climate. Current CVS algorithms based on OCO-2 have to be combined with cloud top height products from CALIPSO and CloudSat, which are no longer available after these two satellites left A-Train in 2018. In this paper, we derive a machine learning-based algorithm using only OCO-2 oxygen A-band hyperspectral measurements to simultaneously predict the cloud optical depth (COD), cloud top pressure (p_top), and cloud pressure thickness (CPT) of single-layer liquid clouds. For validation of real observations, the root mean square errors (RMSEs) of the COD, p_top, and CPT are 7.31 (versus the MYD06_L2), 35.06 hPa, and 26.66 hPa (versus the 2B-CLDCLASS-LIDAR). The new algorithm can also predict CVS parameters trained with p_tops from CALIPSO/CloudSat or CODs from MODIS. Controlled experiments show that known p_tops are more conducive to CPT prediction than known CODs, and experiments with both known CODs and p_tops obtain the best accuracy of RMSE = 20.82 hPa. Moreover, a comparison with OCO2CLD-LIDAR-AUX products that rely on CALIPSO shows that our CVS predictions only using OCO-2 measurements have better CODs for all clouds, better p_tops for clouds with a p_top < 900 hPa, and better CPTs for clouds with a CPT > 30 hPa. Full article

Remote sensing of ocean surface pressure from space is very important, and differential absorption LIDAR and differential absorption radar are only two kinds of remote sensing instruments with this potential. The differential absorption LIDAR works with the integral path mode from the spacecraft in the 400 km low-Earth orbit. The differential optical depth of the oxygen A-band is measured, and then the ocean surface pressure is obtained using a circle-iterative calculation. Performance evaluation of the differential absorption LIDAR model was based on feasibility to the advanced system parameters of the space instrument, whilst weak echo pulse energy at ocean surface yielded random errors in the surface pressure measurement. On the other hand, uncertain atmospheric temperature profiles and water vapor mixture profiles resulted in a primary systematic error in the surface pressure. The error of the surface pressure is sensitive to the jitter of the central frequency of laser emission. Under a strict implementation of the error budget, the time resolution is 6.25 s and the along-orbit distance resolution is 44 km, 625 echoes from ocean surface was cumulatively averaged. Consequently, if the jitter of the central frequency of laser emission exceeded 10 MHz, controlling the error of the surface pressure below 0.1% proved almost hopeless; further, the error could be expected to within 0.1–0.2%; however, the error limited within 0.2–0.3% is an achievable indicator. Full article

Aerosol vertical distribution is decisive and hard to be constrained. It is of great significance for the study of atmospheric climate and environment. Oxygen absorption A-bands (755–775 nm) provide a unique opportunity to acquire vertical aerosol profiles from satellites over a large spatial coverage. To investigate the ability of O₂ A-bands in retrieving aerosol vertical distribution, the dependence of retrieval on satellite observation geometry, spectral resolution, signal-to-noise ratio (SNR), size distribution, and a priori knowledge is quantified using information content theory. This work uses the radiative transfer model UNL to simulate four aerosol modes and the instrument noise model. The simulations show that a small scattering angle leads to an increase in the total amount of observed aerosol profile information, with the degrees freedom of signal (DFS) of a single band increasing from 0.4 to 0.85 at high spectral resolution (0.01 nm). The total DFS value of O₂ A-bands varies accordingly between 1.2–2.3 to 3.8–5.1 when the spectral resolution increases from 1 nm to 0.01 nm. The spectral resolution has a greater impact on DFS value than the impact from SNR (an improvement of roughly 41–53% resulted from the change in spectral resolution and the SNR led to 13–18%). The retrieval is more sensitive to aerosols with a coarse-dominated mode. The improvement in spectral resolution on information acquisition is demonstrated using the DFS and the posterior error at various previous errors and resolutions. Full article

In this study, we analyze the accuracy of the stellar occultation technique to detect the oxygen number density and temperature in near space. Based on the validation of the algorithm related to stellar occultation using a single wavelength of 762 nm, the simulation and inversion are performed using the oxygen absorption A-band, and the results are compared with SABER observations to calculate the deviation. Then, the distribution of the detection accuracy with wavelength, latitude, and altitude is analyzed. The results show that the radiant transmittance of the basic observation varies significantly with wavelength and altitude, and it is not sensitive to a change of latitude. The inversion results of each wavelength at different latitudes can be combined, and it can be seen that the 754–769 nm band is preferred for oxygen and temperature detection. Therefore, analyzing the accuracy results of the specific wavelength 757.84 nm at different latitudes, the temperature accuracy can reach 0.1 K in the stratosphere at both low and high latitudes and 0.6–34 K at middle latitudes. The temperature detection accuracy in the mesosphere at each latitude reaches about a dozen K. The deviation of the inversion results at middle latitudes is larger in the thermosphere, and at the other two latitudes, it is about a few dozen K. From the analysis of relative deviation, excluding the deviation of 95–100 km, the deviation of other altitudes is within the ideal range, and the minimum can reach 0. The accuracy of the oxygen number density increases with latitude, and the relative deviation of the middle and high latitudes is around 10–20%. Based on the above results, it is concluded that the technique of starlight occultation exhibits high accuracy for detecting atmospheric parameters in the near space region, and the results lay the technical foundation for the independent development of stellar occultation. Full article

The oxygen A-band (759–770 nm) is a commonly used band for atmospheric observations. The signal in this band has wide dynamic range and can be used to invert several atmospheric parameters, such as air pressure and atmospheric optical depth, at different altitudes. High-resolution oxygen A-band radiance imaging spectrometer (HARIS) is an imaging spectrometer that operates in the oxygen A-band, which is designed for the observation of the direct solar radiance that passes through the atmosphere. HARIS is a transmissive imaging spectrometer that uses a compact transmissive optical system combined with reflective grating spectroscopy, while an area scan CMOS detector is used as the photosensitive element for the observations. HARIS response is associated with the observed target through a calibration process, which uses a monochromator with a supercontinuum laser for the spectral calibration, an integrating sphere with a spectrophotometer for the radiometric calibration and a meridian for the geometric calibration is employed to correct for distortions. The calibration results show that HARIS has an average spectral resolution of 0.33 nm and a field-of-view of 3.085 × 0.03° with an average spatial sampling interval of 0.0138°. Finally, the performance of HARIS is verified through field tests, in which the solar radiance data with an average signal-to-noise ratio of 438.93 is obtained. Full article

We present a novel passive satellite remote sensing approach for observing the three-dimensional distribution of aerosols emitted from wildfires. This method, called AEROS5P, retrieves vertical profiles of aerosol extinction from cloud-free measurements of the TROPOMI satellite sensor onboard the Sentinel 5 Precursor mission. It uses a Tikhonov–Phillips regularization, which iteratively fits near-infrared and visible selected reflectances to simultaneously adjust the vertical distribution and abundance of aerosols. The information on the altitude of the aerosol layers is provided by TROPOMI measurements of the reflectance spectra at the oxygen A-band near 760 nm. In the present paper, we use this new approach for observing the daily evolution of the three-dimensional distribution of biomass burning aerosols emitted by Australian wildfires on 20–24 December 2019. Aerosol optical depths (AOD) derived by vertical integration of the aerosol extinction profiles retrieved by AEROS5P are compared with MODIS, VIIRS and AERONET coincident observations. They show a good agreement in the horizontal distribution of biomass burning aerosols, with a correlation coefficient of 0.87 and a mean absolute error of 0.2 with respect to VIIRS. Moderately lower correlations (0.63) were found between AODs from AEROS5P and MODIS, while the range of values for this comparison was less than half of that with respect to VIIRS. A fair agreement was found between coincident transects of vertical profiles of biomass burning aerosols derived from AEROS5P and from the CALIOP spaceborne lidar. The mean altitudes of these aerosols derived from these two measurements showed a good agreement, with a small mean bias (185 m) and a correlation coefficient of 0.83. Moreover, AEROS5P observations reveal the height of injection of the biomass burning aerosols in 3D. The highest injection heights during the period of analysis were coincident with the largest fire radiative power derived from MODIS. Consistency was also found with respect to the vertical stability of the atmosphere. The AEROS5P approach provides retrievals for cloud-free scenes over several regions, although currently limited to situations with a dominating presence of smoke particles. Future developments will also aim at observing other aerosol species. Full article

Simultaneous observation of aerosols, water vapor, and clouds is conducive to the analysis of their interactions, and the consistency of observation equipment, instrument performance, and observation time is crucial. Molecular oxygen A-band (758–778 nm) and water vapor absorption band (758–880 nm) are two bands with similar wavelengths, and the hyperspectral remote sensing information of these two bands can be exploited to invert the vertical profile of aerosol and water vapor. In this paper, a double-grating spectrometer system (DGSS) was developed. DGSS uses a telescope system and fiber to introduce multi-angle, double-band sunlight, and it splits light synchronously (non-sequentially) to different positions of the detector through a slit plate and two gratings. The DGSS was calibrated in the laboratory and observed in the external field. The results indicated that the spectral resolution reached 0.06 nm (molecular oxygen A-band, 758–778 nm) and 0.24 nm (water vapor absorption band, 758–880 nm). Meanwhile, the spectra of the two bands (three angles in each band) are not aliased on the detector. Besides, the multi-angle simultaneous observation of the high-resolution spectra of the two bands is realized, which proves the effectiveness of this method. This study will provide a scientific basis for the observation of aerosol, water vapor, and cloud ground-based networks. Full article

Clouds act as a major reflector that changes the amount of sunlight reflected to space. Change in radiance intensity due to the presence of clouds interrupts the retrieval of trace gas or aerosol properties from satellite data. In this paper, we developed a fast and robust algorithm, named the fast cloud retrieval algorithm, using a triplet of wavelengths (469, 477, and 485 nm) of the O₂–O₂ absorption band around 477 nm (CLDTO4) to derive the cloud information such as cloud top pressure (CTP) and cloud fraction (CF) for the Geostationary Environment Monitoring Spectrometer (GEMS). The novel algorithm is based on the fact that the difference in the optical path through which light passes with regard to the altitude of clouds causes a change in radiance due to the absorption of O₂–O₂ at the three selected wavelengths. To reduce the time required for algorithm calculations, the look-up table (LUT) method was applied. The LUT was pre-constructed for various conditions of geometry using Vectorized Linearized Discrete Ordinate Radiative Transfer (VLIDORT) to consider the polarization of the scattered light. The GEMS was launched in February 2020, but the observed data of GEMS have not yet been widely released. To evaluate the performance of the algorithm, the retrieved CTP and CF using observational data from the Global Ozone Monitoring Experiment-2 (GOME-2), which cover the spectral range of GEMS, were compared with the results of the Fast Retrieval Scheme for Clouds from the Oxygen A band (FRESCO) algorithm, which is based on the O₂ A-band. There was good agreement between the results, despite small discrepancies for low clouds. Full article

Previous studies have shown that it is feasible to retrieve multiple cloud properties simultaneously based on the space-borne hyperspectral observation in the oxygen A-band, such as cloud optical depth, cloud-top height, and cloud geometrical thickness. However, hyperspectral remote sensing is time-consuming if based on the precise radiative transfer solution that counts multiple scatterings of light. To speed up the radiation transfer solution in cloud scenarios for nadir space-borne observations, we developed a physical parameterization of hyperspectral reflectance in the oxygen A-band for single-layer water clouds. The parameterization takes into account the influences of cloud droplet forward-scattering and nonlinear oxygen absorption on hyperspectral reflectance, which are improvements over the previous studies. The performance of the parameterization is estimated through comparison with DISORT (Discrete Ordinates Radiative Transfer Program Multi-Layered Plane-Parallel Medium) on the cases with solar zenith angle θ, the cloud optical depth τ_c, and the single-scattering albedo ω in the range of 0 ≤ θ ≤ 75, 5 ≤ τ_c ≤ 50, 0.5 ≤ ω ≤ 1. The relative error of the cloud reflectance is within 5% for most cases, even for clouds with optical depths around five or at strong absorption wavelengths. We integrate the parameterization with a slit function and a simplified atmosphere to evaluate its performance in simulating the observed cloud reflection at the top of the atmosphere by OCO-2 (Orbiting Carbon Observatory-2). To better visualize the possible errors from the new parameterization, gas molecular scattering, aerosol scattering, and reflection from the underlying surface are ignored. The relative error of the out-of-band radiance is less than 4% and the relative error of the intra-band radiance ratio is less than 4%. The radiance ratio is the ratio of simulated observations with and without in-cloud absorption and is used to assess the accuracy of the parameterization in quantifying the in-cloud absorption. The parameterization is a preparation for rapid hyperspectral remote sensing in the oxygen A-band. It would help to improve retrieval efficiency and provide cloud geometric thickness products. Full article

With three imaging grating spectrometers, the Orbiting Carbon Observatory-2 (OCO-2) measures high spectral resolution spectra ( $\lambda /\Delta \lambda \approx$ 19,000) of reflected solar radiation within the molecular oxygen (O ${}_2$ ) A-band at 0.765 $\mathsf{\mu }$ m and two carbon dioxide (CO ${}_2$ ) bands at 1.61 and 2.06 $\mathsf{\mu }$ m. OCO-2 uses onboard lamps with a reflective diffuser, solar observations through a transmissive diffuser, lunar measurements, and surface targets for radiometric calibration and validation. Separating calibrator aging from instrument degradation poses a challenge to OCO-2. Here we present a methodology for trending the OCO-2 Build 8R radiometric calibration using OCO-2 nadir observations over eight desert sites and nearly simultaneous observations from Moderate Resolution Imaging Spectroradiometer (MODIS) with sensor viewing zenith angles of 15 ± 0.5 ${}^{\circ }$ . For the O ${}_2$ A-band, this methodology is able to quantify a drift of −0.8 ± 0.1% per year and capture a small error in correcting the aging of the solar calibrator. For the other two OCO-2 bands, no measurable changes were seen, indicating less than 0.1% and less than 0.3% per year drift in the radiometric calibration of Band 2 and Band 3, respectively. Full article