Search Results (13)

The Geostationary Interferometric Infrared Sounder (GIIRS) onboard the FengYun-4B weather satellite provides critical upwelling atmospheric infrared radiance. To address the limitations of the previous sounder (FY-4A/GIIRS) in terms of spatial resolution and spectral coverage, FY-4B/GIIRS has increased the spatial resolution to 12 km and added more spectral channels in the long-wave band to enhance the observation details and information content of weather systems. To evaluate its baseline performance, a comprehensive preflight test campaign—encompassing spectral and radiometric assessments—was conducted in a thermal vacuum (TVAC) chamber. Spectral characterization via laser measurements confirmed the instrument spectral response function (ISRF) is highly consistent with the theoretical cardinal sine function (sinc). Gas-cell tests demonstrated that, after correcting for off-axis effect, the spectral calibration errors are on average less than 5 ppm, validated against Line-By-Line Radiative Transfer Model (LBLRTM) simulations. The radiometric calibration employed temperature-variable blackbodies for noise performance and radiometric accuracy assessments. The radiometric sensitivity, characterized by Noise Equivalent differential Radiance (NEdR), is less than 0.5 and 0.1 mW/(m²·sr·cm⁻¹) in the long-wave infrared (LWIR) and mid-wave infrared (MWIR) bands, respectively. To address the LWIR detector nonlinearity, an iterative polynomial fitting algorithm based on spectral responsivity invariance was implemented. This correction reduces the radiometric deviation from >1.0 K to ~0.2 K, meeting the 0.7 K accuracy requirement across a 180–315 K dynamic range. Conversely, the MWIR band exhibits high linearity but is limited by noise when observing low-temperature scenarios and can only meet the 0.7 K requirement within the range of 250 to 315 K. Full article

This paper compares the following four Terahertz (THz) band molecular absorption loss modeling tools: International Telecommunication Union (ITU)-R P.676 model, Line-by-Line Radiative Transfer Model (LBLRTM), Atmospheric Model (am), and HITRAN on the Web (HotW). We evaluate the THz band drone communication tools under horizontal and vertical communication scenarios. We use the U.S. Standard 1976 and tropical weather profiles to generate path loss data across different altitudes, frequencies, and distances. We also employ a simple analytical model, fitting the data from the ITU, LBLRTM, and am tools to assess its accuracy in predicting path loss. Our results demonstrate high consistency among the tools, with path loss differences becoming more significant in vertical scenarios. This study provides the first comprehensive comparison of four widely used molecular absorption loss modeling tools for THz band drone communications, considering various scenarios and weather conditions. Full article

Atmospheric water vapor plays a significant impact on the climate system, radiative transfer models, and optoelectronic engineering applications. Fast and accurate calculation of its optical depth and transmittance is a crucial step to studying the radiation characteristics of water vapor. Although the traditional physics-based, line-by-line radiative transfer model (LBLRTM) meets the accuracy requirements, it is too slow and computationally expensive for practical applications. In this study, to facilitate the accuracy and efficiency requirements of atmospheric water vapor optical depth and transmittance calculation, we propose a Stack LSTM-AT model that combines a double-layer Long Short-Term Memory (LSTM) network and a self-attention mechanism method, and different configurations of the hybrid model are extensively examined. The results show that, compared to the LBLRTM model, the Stack LSTM-AT model significantly improves computational efficiency while maintaining accuracy. Overall, the R-squared, mean absolute error (MAE), and root mean square error (RMSE) of optical depth is 0.9999945, 0.00568, and 0.02033, respectively, while the R-squared, MAE, and RMSE of atmospheric transmittance is 0.9999964, 5.5586 × 10⁻⁴, and 9.4 × 10⁻⁴, respectively. Moreover, the difference in optical depths and transmittance between the prediction results of the Stack LSTM-AT model and the calculation results of the LBLRTM are no greater than 0.3 and 0.008, respectively, across various pressures, temperatures, and water vapor amounts. The computation time for calculating the transmittance of a single spectrum (1–5000 cm⁻¹) is about 9.784 × 10⁻² s, with a spectrum resolution of 1 cm⁻¹, which is about 1000 times faster than that of LBLRTM. The proposed Stack LSTM-AT model could significantly enhance the efficiency and accuracy of atmospheric radiative transfer simulations, demonstrating its broad potential in real-time meteorological monitoring and atmospheric component inversion. This study may provide new insights and technical support for the study of radiative transfer, climate change, and atmospheric environmental monitoring. Full article

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

The Atmospheric Radiative Transfer Simulator (ARTS) has been widely used in the radiation transfer simulation from microwave to terahertz. Due to the same physical principles, ARTS can also be used for simulations of thermal infrared (TIR). However, thorough evaluations of ARTS in the TIR region are still lacking. Here, we evaluated the performance of ARTS in 600–1650 cm⁻¹ taking the Line-By-Line Radiative Transfer Model (LBLRTM) as a reference model. Additionally, the moderate resolution atmospheric transmission (MODTRAN) band model (BM) and correlated-k (CK) methods were also used for comparison. The comparison results on the 0.001 cm⁻¹ spectral grid showed a high agreement (sub-0.1 K) between ARTS and LBLRTM, while the mean bias difference (MBD) and root mean square difference (RMSD) were less than 0.05 K and 0.3 K, respectively. After convolving with the spectral response functions of the Atmospheric Infra-Red Sounder (AIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS), the brightness temperature (BT) differences between ARTS and LBLRTM became smaller with RMSDs of <0.1 K. The comparison results for Jacobians showed that the Jacobians calculated by ARTS and LBLRTM were close for temperature (can be used for Numerical Weather Prediction application) and O₃ (excellent Jacobian fit). For the water vapor Jacobian, the Jacobian difference increased with an increasing water vapor content. However, at extremely low water vapor values (0.016 ppmv in this study), LBLRTM exhibited non-physical mutations, while ARTS was smooth. This study aims to help users understand the simulation accuracy of ARTS in the TIR region and the improvement of ARTS via the community. Full article

Monitoring global greenhouse gas concentration information via satellite remote sensing has become a critical area of research to support the further understanding of global carbon emissions. The Greenhouse-gases Absorption Spectrometer-2 (GAS-2) is being developed as the primary payload of the Fengyun-3H (FY-3H), which will be launched in 2024. Achieving high-precision mesurements of greenhouse gases requires precise spectral calibration. However, currently, there is no method for assessing the detection accuracy of GAS-2 using spectral calibration light sources, and quantitative studies are lacking. In this study, the influence model of calibration light sources on spectral calibration accuracy is established, and the spectral radiance acquired via GAS-2 is simulated using the line-by-line radiative transfer model (LBLRTM). We investigated the impact of different linewidths and wavelength stabilities of the calibration light source on its accuracy in four wavelength bands. This study is the first to examine the effects of the linewidth and wavelength stability of a calibration light source on the spectral radiance acquired via GAS-2. The initial results demonstrate that if the linewidth of the calibration light source is approximately 100 MHz and the wavelength stability is in the order of subpicometers, the radiance error obtained by GAS-2 is less than 10%. Among the four bands, the 2.06 $\mathsf{\mu }$m (strong-$C{O}_2$) band is more affected by the calibration light source than the other three bands. In addition, the wavelength stability of the light source has a greater influence on the error than the linewidth of the light source under the same error condition. The research findings can be used to guide and reference the selection of light sources in the laboratory spectral calibration of GAS-2, ultimately contributing to the instrument’s quantitative development level. Full article

In 2019 the Far-Infrared Outgoing Radiation Understanding and Monitoring (FORUM) mission was selected to be the 9th Earth Explorer mission of the European Space Agency (ESA). In the preparatory phase of the mission there was the need for accurate and versatile codes to compute the spectrally resolved Earth radiation escaping to space ( outgoing long-wave radiation, OLR), targets for the FORUM measurements.Moreover, for the study of planetary atmospheres, several instruments measuring the planetary radiation escaping to space have been deployed (i.e., the planetary Fourier spectrometer on Mars express or composite infrared spectrometer on Cassini). For both the analysis of the measurements of these instruments and the design of new instruments, reliable radiative transfer codes need to be available. In this paper, we describe two full physics codes, Geofit broadband-Nadir (GBB-Nadir) and Kyoto protocol-informed management of adaptation (KLIMA), both able to compute the OLR spectrum, while GBB-Nadir is only a forward model, and therefore computes the spectra only, KLIMA implements the computation of spectral radiance derivatives with respect to atmospheric parameters and therefore it is suitable to be used in retrieval codes. The GBB-Nadir code can be interfaced with radiative transfer solvers that include representations of multiple scatterings, making it suitable to compute the radiances in all-sky conditions. KLIMA has been extensively validated comparing its radiances to ones generated by the widely used line-by-line radiative transfer model (LBLRTM) code. In this paper, we describe the latest version of both codes and their comparison. We compared the optical depth computed by GBB-Nadir and KLIMA for given values of pressure, temperature and gas columns for most gases active in the far-infrared and thermal-infrared spectral regions. We show that the optical depths computed by the two codes are in very good agreement. We compared the simulated spectra in clear sky conditions for three different atmospheres (equatorial, mid-latitude and polar) at resolutions of the FORUM instrument. The differences found are well below the expected noise of the FORUM instrument. The KLIMA code has already been used to simulate the observations of the Mars atmosphere, while the limb version of the GBB code has been used to simulate the radiances measured in the limb geometry of planetary atmospheres (Titan and Jupiter). Therefore, we may safely affirm that both codes can be used to simulate the nadir measurements of planetary atmospheres. Full article

This paper provides a procedure for the simulation of radiances from the U. S. National Oceanic and Atmospheric Administration (NOAA) Cross-track Infrared Sounder (CrIS) Fourier Transform Spectrometer to include spectral ringing effects caused by the finite-band, non-flat instrument spectral response to incident radiation. A simulation using a line-by-line radiative transfer model is performed to illustrate the magnitude of the effect and to indicate which spectral channels are likely to be impacted. Comparisons with CrIS observations are made to show that for most channels this effect is negligibly small compared to errors in the radiative transfer calculations but for the longwave edge of the CrIS longwave band and a few other regions, the brightness temperature ringing is significant. While the ringing artifact described in this paper may appear to be removed when Hamming apodization is applied, as is done for the assimilation of CrIS data into Numerical Weather Prediction (NWP) models, it is still present, and its influence reappears if the spectral correlation induced by apodization is properly handled to preserve the information content that derives from high spectral resolution. Inclusion of the instrument responsivity in calculated spectra to properly mimic the observed spectra as defined here eliminates artifacts from this type of ringing. Users of CrIS radiances should consider whether this effect is important for their application. Full article

The atmospheric temperature and humidity profiles of the troposphere are generally measured by radiosondes and satellites, which are essential for analyzing and predicting weather. Nevertheless, the insufficient observation frequencies and low detection accuracy of the boundary layer restricts the description of atmospheric state changes by the temperature and humidity profiles. Therefore, this work focus on retrieving the temperature and humidity profiles using observations of the FengYun-4 (FY-4) Geostationary Interferometric Infrared Sounder (GIIRS) combined with ground-based infrared spectral observations from the Atmospheric Emitted Radiance Interferometer (AERI), which are more accurate than space-based individual retrieval results and have a wider effective retrieval range than ground-based individual retrieval results. Based on the synergistic observations, which are made by matching the space-based and ground-based data with those of different spatial and temporal resolutions, a synergistic retrieval process is proposed to obtain the temperature and humidity profiles at a high frequency under clear-sky conditions based on the optimal estimation method. In this research, using the line-by-line radiative transfer model (LBLRTM) as the forward model for observing simulations, a retrieval experiment was carried out in Qingdao, China, where an AERI is situated. Taking radiosonde data as a reference for comparing the retrieval results of the temperature and humidity profiles of the troposphere, the root-mean-square error (RMSE) of the synergistic retrieval algorithm below 400 hPa is within 2 K for temperature and within 12% for relative humidity. Compared with the GIIRS individual retrieval, the RMSE of temperature and relative humidity for the synergistic method is reduced by 0.13–1.5 K and 2.7–4.4% at 500 hPa, and 0.13–2.1 K and 2.5–7.2% at 900 hPa. Moreover, the forecast index (FI) calculated from the retrieval results shows reasonable consistency with the FIs calculated from the ERA5 reanalysis and from radiosonde data. The synergistic retrieval results have higher temporal resolution than space-based retrieval results and can reflect the changes in the atmospheric state more accurately. Overall, the results demonstrated the promising potential of the synergistic retrieval of temperature and humidity profiles at high accuracy and high temporal resolution under clear-sky conditions from FY-4/GIIRS and AERI. Full article

Remote sensing of HDO and CH₄ could provide valuable information on environmental and climatological studies. In a recent contribution, we reported a 3.53 μm distributed feedback (DFB) inter-band cascade laser (ICL)-based heterodyne radiometer. In the present work, we present the details of measurements and inversions of HDO and CH₄ at Dunhuang, Northwest of China. The instrument line shape (ILS) of laser heterodyne radiometer (LHR) is discussed firstly, and the spectral resolution is about 0.004 cm⁻¹ theoretically according to the ILS. Furthermore, the retrieval algorithm, optimal estimation method (OEM), combined with LBLRTM (Line-by-line Radiative Transfer Model) for retrieving the densities of atmospheric HDO and CH₄ are investigated. The HDO densities were retrieved to be less than 1.0 ppmv, while the CH₄ densities were around 1.79 ppmv from 20 to 24 July 2018. The correlation coefficient of water vapor densities retrieved by LHR and EM27/SUN is around 0.6, the potential reasons for the differences were discussed. Finally, in order to better understand the retrieval procedure, the Jacobian value and the Averaging Kernels are also discussed. Full article

The alternate mapping correlated k-distribution (AMCKD) method is studied and applied to satellite simulations. To evaluate the accuracy of AMCKD, the simulated brightness temperatures at the top of the atmosphere are compared with line-by-line radiative transfer model (LBLRTM) or the observed data which are from Advanced Himawari Imager (AHI) on board the Himawari-8, as well as Medium Resolution Spectral Imager (MERSI) on board the Fengyun-3D. The result of AMCKD is also compared with the algorithm of Radiative Transfer for the Television Observation Satellite Operational Vertical Sounder (RTTOV). Under the standard atmospheric profiles, the absolute errors of AMCKD in all longwave channels of AHI and MERSI are bounded by 0.44K compared to the benchmark results of LBLRTM, which are more accurate than those of RTTOV. In the most cases, the error of AMCKD is smaller than the NEDT at ST, while the error of RTTOV is larger than the instrument noise equivalent temperature (NEDT) at scene temperature (ST). Under real atmospheric profile conditions, the errors of AMCKD increase, because the input data from ERA-Interim reanalysis dataause bias in the satellite remote sensing results. In the most considered cases, the accuracy of AMCKD is higher than RTTOV, while the efficiency of AMCKD is slightly slower than RTTOV. Full article

Nitrogen trifluoride (NF₃) has the potential to make a growing contribution to the Earth’s radiative budget. In this study, the global mean radiative efficiency of NF₃ is calculated as 0.188 W·m⁻²·ppb⁻¹ by line-by-line method. Global warming potentials of 14,700 for 100 years and global temperature potentials of 16,600 for 100 years are calculated. At the same time, inhomogeneous instantaneous radiative forcing of NF₃ at the top of the atmosphere and its relationship to other atmospheric and surface variables are studied. A total of 42 atmospheric profiles are used. The results show NF₃ instantaneous radiative efficiency range from 0.07 W·m⁻²·ppb⁻¹ to 0.50 W·m⁻²·ppb⁻¹ in clear sky conditions. The mean value is 0.25 W·m⁻²·ppb⁻¹. In clear sky conditions, the correlation coefficient between surface temperature and NF₃ instantaneous radiative forcing is 0.94 and the partial correlation coefficient is −0.88 between integrated water content and NF₃ instantaneous radiative forcing. A regression model is constructed for NF₃ instantaneous radiative forcing based on surface temperature and integrated water content. The average value of the relative error is 6.17% based on LBLRTM (Line-by-Line Radiative Transfer Model) results. The correlation coefficient is 0.985 between cloud radiative forcing and the difference of NF₃ instantaneous radiative forcing between clear sky and all cloudy sky conditions. A regression model is constructed for NF₃ instantaneous radiative forcing in all cloudy sky. The average relative error is 5.9% based on LBLRTM results. Full article

Modern satellite radiometers have many detectors with different relative spectral response (RSR). Effect of RSR differences on striping and the root cause of striping in sensor data record (SDR) radiance and brightness temperature products have not been well studied. A previous study used MODTRAN radiative transfer model (RTM) to analyze striping. In this study, we make efforts to find the possible root causes of striping. Line-by-Line RTM (LBLRTM) is used to evaluate the effect of RSR difference on striping and the atmospheric dependency for VIIRS bands M15 and M16. The results show that previous study using MODTRAN is repeatable: the striping is related to the difference between band-averaged and detector-level RSR, and the BT difference has some atmospheric dependency. We also analyzed VIIRS earth view (EV) data with several striping index methods. Since the EV data is complex, we further analyze the onboard calibration data. Analysis of Variance (ANOVA) test shows that the noise along track direction is the major reason for striping. We also found evidence of correlation between solar diffuser (SD) and blackbody (BB) for detector 1 in M15. Digital Count Restoration (DCR) and detector instability are possibly related to the striping in SD and EV data, but further analysis is needed. These findings can potentially lead to further SDR processing improvements. Full article