Advances in Infrared Observation of Earth's Atmosphere

This study provides an in-depth analysis of the characteristics of stellar occultation events. Using 10 target star sources, the influence of orbital elements on the number, duration, and distribution of stellar occultation events was simulated and analyzed, and the constellation configuration was designed. The results showed the following points: (1) the orbital inclination had the greatest influence on the number of occultation events, with obvious upward and downward trends in the range of 10–40° and 150–180°, and the amount of occultation data remained at about 303 times under the other angle conditions. The orbital height had an effect on the number of occultations, but the amplitude was small. (2) The use of four orbits had an impact on the occultation duration. The duration decreased with an increase in the orbit height and inclination, the distribution was symmetrical with the perigee angular distance, and it increased with an increase in the ascending intersection right ascension. (3) The higher the orbital height, the less comprehensive the longitudinal and latitudinal distribution of occultation events. With an orbital inclination of less than 150°, the greatest occultation event was covered to encompass the entire world. The other two orbital elements had negligible effects on the longitudinal and latitudinal distribution of occultation events. (4) The elevation of the occultation event increased with an increase in the orbital altitude, but the azimuth showed no obvious change trends. A considerable number of normal occultations can be obtained with an orbital inclination of less than 120°. The other two orbital elements had a negligible effect on the distribution of altitude and azimuth of occultation events. A stellar occultation constellation configuration was designed based on the simulation results, and the results showed that the following parameters of satellites can be used to realize the global distribution of occultation events: orbital height of 500 km, orbital inclination of 97.3771°, perigee angular distance of 40°, and ascending node right ascension steps of 40°. This configuration will ensure that an adequate number of normal occultations are obtained, which will ensure the quality of data inversion under the condition of 152 infrared target star sources. Full article

Before infrared hyperspectral data are used in satellite data assimilation systems or retrieval systems, the quantitative analysis of data deviation is necessary. Based on RTTOV’s (Radiative Transfer for TOVS) simulation data of FY-3E/HIRAS-II (Hyperspectral Infrared Atmospheric Sounder) and the observation data of HIRAS-II, we counted the bias of observation minus simulation (OMB) during an on-orbit test; analyzed the characteristics and reasons for the bias from the perspective of the FOV (field of view), the scanning angle of the instrument, the day and night, and the target temperature change; and analyzed the stability of the radiometric calibration accuracy. We also combined the results of the MetOp-C/IASI (infrared atmospheric sounding interferometer), a similar high-precision instrument, with the bias of OMB to compare and evaluate the FY-3E/HIRAS-II radiometric calibration accuracy. In the end, we found that the mean OMB bias of the long-wave and medium-wave infrared bands is within ±2 K, and the bias standard deviation is better than 2 K; the bias of each FOV is consistent and the bias of most channels is better than 2 K. The OMB bias of each channel is consistent with the changes in the angle of the instrument. The bias trend of long-wave and medium-wave infrared channels is more consistent with the deviation of the day and night; the bias of the short-wave infrared channel at night is lower than in the daytime. When counting the bias as the target temperature changed, the results showed that there are no obvious temperature dependencies in the long-wave and medium-wave infrared channels. This reflects that the instrument’s non-linear effect is well ordered. We further evaluated the stability of the radiometric calibration accuracy through statistics from the OMB standard deviation of each channel of FY-3E/HIRAS-II. Most channel accuracy stability values were better than 0.1 K. We calculated that IASI and HIRAS-II OMB have double differences, and the results show that the double difference in most channels is better than 1 K. It shows that the HIRAS-II and IASI observations are highly consistent. Through the statistics of the OMB bias during the on-orbit test period of FY-3E/HIRAS-II, we fully evaluated its radiometric calibration accuracy and laid the foundation for FY-3E/HIRAS-II data to be used in the retrieval application and assimilation system. Full article

Nitrous oxide (N${}_2$O) is a greenhouse gas difficult to estimate by satellite because of its weak spectral signature in the infra-red band and its low variability in the troposphere. Nevertheless, this study presents the evaluation of new tropospheric N${}_2$O observations from the Infrared Atmospheric Sounder Interferometer (IASI) on Metop-A using the Toulouse N${}_2$O Retrieval Version 2.0 tool. This tool is based on the Radiative Transfer for Tiros Operational Vertical sounder (RTTOV) model version 12.3 coupled to the Levenberg-Marquardt optimal estimation method enabling the simultaneous retrieval of methane, water vapour, temperature profiles together with surface temperature and emissivity within the 1240–1350 cm${}^{-1}$ window. In this study, we focused on the upper troposphere (300 hPa) where the sensitivity of IASI is significant. The IASI N${}_2$O data has been evaluated using aircraft N${}_2$O observations from the High-performance Instrumented Airborne Platform for Environmental Research Pole-to-Pole Observations (HIPPO) campaigns in 2009, 2010, and 2011 and from the National Oceanic and Atmospheric Administration’s (NOAA) Global Greenhouse Gas Reference Network (GGGRN) in 2011. In addition, we evaluated the IASI N${}_2$O using ground-based N${}_2$O measurements from 9 stations belonging to the Network for the Detection of Atmospheric Composition Change (NDACC). We found a total random error of ∼2 ppbv (0.6%) for one single retrieval at 300 hPa. Under favorable conditions, this error is also found in the vertical level pressure range 300–500 hPa. It decreases rapidly to ∼0.4 ppbv (0.1%) when we average on a 1° × 1° box. In addition, independent observations allows the estimation of bias with the IASI TN${}_2$OR v2.0 N${}_2$O. The bias between IASI and aircraft N${}_2$O data at 300 hPa is ∼1.0 ppbv (∼0.3%). We found an estimated random error of ∼2.3 ppbv (∼0.75%). This study also shows relatively high correlations between IASI data and aircraft in situ profiles but more varying correlations over the year 2011 depending on the location between IASI and NDACC remote sensing data. Finally, we present daily, monthly, and seasonal IASI N${}_2$O horizontal distributions in the upper troposphere as well as cross sections for different seasons that exhibit maxima in the Tropical band especially over Africa and South America. Full article

The Greenhouse Gases Monitoring Instrument (GMI), on board the Chinese Gaofen-5 (GF-5) satellite, provides rich observation data for the global remote sensing of atmospheric CO₂. To meet the high-precision satellite retrieval needs of atmospheric CO₂, this paper designs a coupled bidirectional reflectance distribution function (BRDF) CO₂ retrieval (CBCR) method, which describes the surface reflectance characteristics by the BRDF, corrects for atmospheric scattering based on full physics retrieval theory, and ensures the stable retrieval of multiple parameters and atmospheric CO₂ by enriching prior constraints. Theoretical analysis shows that the influence of atmospheric scattering induced by the surface bidirectional reflectance characteristics is significantly related to the aerosol optical depth (AOD), solar zenith angle (SZA), and viewing zenith angle (VZA). The validation of GMI CO₂ retrievals shows that the CBCR method significantly reduced the influence of the surface bidirectional reflectance characteristics under high AOD and high SZA conditions, decreased the atmospheric CO₂ retrieval error from 0.58 ± 5.64 ppm to −1.33 ± 3.13 ppm, and increased the correlation with the temporal variation of actual atmospheric CO₂ from 34.7 to 76.8%. Our CBCR method can correct the influence of atmospheric scattering induced by the surface bidirectional reflectance characteristics on atmospheric CO₂ retrieval, and this work demonstrates that describing the surface reflectance characteristics by using BRDF is a promising idea in the field of satellite CO₂ retrievals. Full article

FY-4A/GIIRS (Geosynchronous Interferometric Infrared Sounder) is the first infrared hyperspectral atmospheric vertical detector in geostationary orbit. Compared to other similar instruments, it has the advantages of high temporal resolution and stationary relative to the ground. Based on the characteristics of GIIRS observation data, we proposed a humidity profile retrieval method. We fully utilized the information provided by the observation and forecast data, and used the two-dimensional brightness temperature data with the dimension of time and optical spectrum as the input of the CNN (convolution neural network model). Then, the obtained brightness temperature data were shown to be more suitable as the input for the physical retrieval method for humidity than the conventional correction method, improving the accuracy of humidity profile retrieval. We performed two comparative experiments. The first experiment results indicate that, compared to ordinary linear correction and ANN (artificial neural network algorithm) correction, our revised observed brightness temperature data are much closer to the simulated brightness temperature obtained by inputting ERA5 reanalysis data into RTTOV (Radiative Transfer for TOVS). The results of the second experiment indicate that the accuracy of the humidity profile retrieved by our method is higher than that of conventional ANN and 1D-Var (one-dimensional variational algorithm). With ERA5 reanalysis data as the reference value, the RMSE (Root Mean Squared Error) of the humidity profiles by our method is less than 8.2% between 250 and 600 hPa. Our method holds the unique advantage of the high temporal resolution of GIIRS, improves the accuracy of humidity profile retrieval, and proves that the combination of machine learning and the physical method is a compelling idea in the field of satellite atmospheric remote sensing worthy of further exploration. Full article

We present the first analysis of water vapour profiles derived from nadir measurements by the infrared imaging Fourier transform spectrometer GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere). The measurements were performed on 27 September 2017, during the WISE (Wave driven ISentropic Exchange) campaign aboard the HALO aircraft over the North Atlantic in an area between 37°–50°N and 20°–28°W. From each nadir recording of the 2-D imaging spectrometer, the spectral radiances of all non-cloudy pixels have been averaged after application of a newly developed cloud filter. From these mid-infrared nadir spectra, vertical profiles of H${}_2$O have been retrieved with a vertical resolution corresponding to five degrees of freedom below the aircraft. Uncertainties in radiometric calibration, temperature and spectroscopy have been identified as dominating error sources. Comparing retrievals resulting from two different a priori assumptions (constant exponential vs. ERA 5 reanalysis data) revealed parts of the flight where the observations clearly show inconsistencies with the ERA 5 water vapour fields. Further, a water vapour inversion at around 6 km altitude could be identified in the nadir retrievals and confirmed by a nearby radiosonde ascent. An intercomparison of multiple water vapour profiles from GLORIA in nadir and limb observational modes, IASI (Infrared Atmospheric Sounding Interferometer) satellite data from two different retrieval processors, and radiosonde measurements shows a broad consistency between the profiles. The comparison shows how fine vertical structures are represented by nadir sounders as well as the influence of a priori information on the retrievals. Full article

Vertical profiles and stratospheric HNO₃ and HCl columns are retrieved by ground-based high resolution Fourier transform infrared spectroscopy (FTIR) remote sensing measurements at the Hefei site in China. The time series of stratospheric HNO₃ and HCl columns from January 2017 to December 2019 showed similar annual variation trends, with an annually decreasing rate of (−9.45 ± 1.20)% yr⁻¹ and (−7.04 ± 0.81)% yr⁻¹ for stratospheric HNO₃ and HCl, respectively. The seasonal amplitudes of stratospheric HNO₃ and HCl are 2.67 × 10¹⁵ molec cm⁻² and 4.76 × 10¹⁴ molec cm⁻² respectively, both reaching their maximum in March and their minimum in September, due to the tropopause height variation. Further, HNO₃ and HCl data were used to compare with Microwave Limb Sounder (MLS) satellite data. MLS satellite data showed similar seasonal variations and annual rates with FTIR data, and the stratospheric HNO₃ and HCl columns of the two datasets have correlation coefficients (r) of 0.87 and 0.88, respectively. The mean bias between satellite and FTIR data of stratospheric HNO₃ and HCl columns are (−8.58 ± 12.22)% and (4.58 ± 13.09)%, respectively. Full article

Satellite infrared hyperspectral instruments can obtain a wealth of atmospheric spectrum information. In order to obtain high-precision atmospheric temperature and humidity profiles, we used the traditional One-Dimensional Variational (1D-Var) retrieval algorithm, combined with the information capacity-weight function coverage method to select the spectrum channel. In addition, an Artificial Neural Network (ANN) algorithm was introduced to correct the satellite observation data error and compare it with the conventional error correction method. Finally, to perform the temperature and humidity profile retrieval calculation, we used the FY-3D satellite HIRAS (Hyperspectral Infrared Atmospheric Sounder) infrared hyperspectral data and combined the RTTOV (Radiative Transfer for TOVS) radiative transfer model to build an atmospheric temperature and humidity profile retrieval system. We used data on the European region from July to August 2020 to carry out the training and testing of the retrieval system, respectively, and used the balloon-retrieved sounding data of temperature and humidity published by the University of Wyoming as standard truth values to evaluate the retrieval accuracy. Our preliminary research results show that, compared with the retrieval results of conventional deviation correction, the introduction of ANN algorithm error correction can improve the retrieval accuracy of the retrieval system effectively and the RMSE (Root-Mean-Square Error) of the temperature and humidity has a maximum accuracy of improvement of about 0.5 K (The K represents the thermodynamic temperature unit) and 5%, respectively. The temperature and humidity results obtained by the retrieval system were compared with Global Forecast System (GFS) forecast data. The retrieved temperature RMSE was less than 1.5 K on average, which was better than that for the GFS; the humidity RMSE was less than 15% as a whole, and better than the forecast profile between 100 hpa (1 hpa is 100 pa, the pa represents the air pressure unit) and 600 hpa. Compared with AIRS (Atmospheric Infrared Sounder) products, the result of the retrieval system also had a higher accuracy. The main improvement of the temperature was at 200 hpa and 800 hpa, with maximum accuracy improvements of 2 K and 1.5 K, respectively. The RMSE of the humidity retrieved by the system was also better than the AIRS humidity products at most pressure levels, and the error of maximum difference could reach 15%. After combining the two algorithms, the FY-3D/HIRAS infrared hyperspectral retrieval system could obtain higher-precision temperature and humidity profiles, and relevant results could provide a reference for improving the accuracy of business products. Full article

We examined methane (CH₄) variability over different regions of India and the surrounding oceans derived from thermal infrared (TIR) band observations (TIR CH₄) by the Thermal and Near-infrared Sensor for carbon Observation—Fourier Transform Spectrometer (TANSO-FTS) onboard the Greenhouse gases Observation SATellite (GOSAT) for the period 2009–2014. This study attempts to understand the sensitivity of the vertical profile retrievals at different layers of the troposphere and lower stratosphere, on the basis of the averaging kernel (AK) functions and a priori assumptions, as applied to the simulated concentrations by the MIROC4.0-based Atmospheric Chemistry-Transport Model (MIROC4-ACTM). We stress that this is of particular importance when the satellite-derived products are analyzed using different ACTMs other than those used as retrieved a priori. A comparison of modeled and retrieved CH₄ vertical profiles shows that the GOSAT/TANSO-FTS TIR instrument has sufficient sensitivity to provide critical information about the transport of CH₄ from the top of the boundary layer to the upper troposphere. The mean mismatch between TIR CH₄ and model is within 50 ppb, except for the altitude range above 150 hPa, where the sensitivity of TIR CH₄ observations becomes very low. Convolved model profiles with TIR CH₄ AK reduces the mismatch to less than the retrieval uncertainty. Distinct seasonal variations of CH₄ have been observed near the atmospheric boundary layer (800 hPa), free troposphere (500 hPa), and upper troposphere (300 hPa) over the northern and southern regions of India, corresponding to the southwest monsoon (July–September) and post-monsoon (October–December) seasons. Analysis of the transport and emission contributions to CH₄ suggests that the CH₄ seasonal cycle over the Indian subcontinent is governed by both the heterogeneous distributions of surface emissions and the influence of the global monsoon divergent wind circulations. The major contrast between monsoon, and pre- and post-monsoon profiles of CH₄ over Indian regions are noticed near the boundary layer heights, which is mainly caused by seasonal change in local emission strength with a peak during summer due to increased emissions from the paddy fields and wetlands. A strong difference between seasons in the middle and upper troposphere is caused by convective transport of the emission signals from the surface and redistribution in the monsoon anticyclone of upper troposphere. TIR CH₄ observations provide additional information on CH₄ in the region compared to what is known from in situ data and total-column (XCH₄) measurements. Based on two emission sensitivity simulations compared to TIR CH₄ observations, we suggest that the emissions of CH₄ from the India region were 51.2 ± 4.6 Tg year⁻¹ during the period 2009–2014. Our results suggest that improvements in the a priori profile shape in the upper troposphere and lower stratosphere (UT/LS) region would help better interpretation of CH₄ cycling in the earth’s environment. Full article

In our study, a retrieval method of temperature profiles is proposed which combines an improved one-dimensional variational algorithm (1D-Var) and artificial neural network algorithm (ANN), using FY-4A/GIIRS (Geosynchronous Interferometric Infrared Sounder) infrared hyperspectral data. First, according to the characteristics of the FY-4A/GIIRS observation data using the conventional 1D-Var, we introduced channel blacklists and discarded the channels that have a large negative impact on retrieval, then used the information capacity method for channel selection and introduced a neural network to correct the satellite observation data. The improved 1D-Var effectively used the observation information of 1415 channels, reducing the impact of the error of the satellite observation and radiative transfer model, and realizing the improvement of retrieval accuracy. We subsequently used the improved 1D-Var and ANN algorithms to retrieve the temperature profiles, respectively, from the GIIRS data. The results showed that the accuracy when using ANN is better than using improved 1D-Var in situations where the pressure ranges from 800 hPa to 1000 hPa. Therefore, we combined the improved 1D-Var and ANN method to retrieve temperature profiles for different pressure levels, calculating the error by taking sounding data published by the University of Wyoming as the true values. The results show that the average error of the retrieved temperature profiles is smaller than 2 K when using our method, this method makes the accuracy of the retrieved temperature profiles superior to the accuracy of the GIIRS products from 10 hPa to 575 hPa. All in all, through the combination of the physical retrieval method and the machine learning retrieval method, this paper can certainly provide a reference for improving the accuracy of products. 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 time constant selected for lock-in amplification (LIA) has a crucial impact on observed line shapes in laser heterodyne spectroscopy, in particular in the case of ground-based remote monitoring of trace gas in the atmospheric column using laser heterodyne radiometer (LHR). Conventional simulation could not allow validation of LHR spectra measured in a real and complex atmospheric environment exhibiting large temporal and spatial variability (humidity, temperature, pressure, etc) that impact significantly the measured LHR spectra profiles. High-precision spectral measurement is thus crucial to avoid any spectral distortion resulting from the measurement. In this paper, the impact of LIA time constant on spectral line shape is investigated for LHR operating in continuous laser tuning mode, based on analysis of laboratory heterodyne spectra, in terms of signal-to-noise ratio (SNR), line width broadening, absorption depth and line shift. With respect to the given frequency scanning speed in continuous mode and to the halfwidth of the absorption feature to scan, a reasonable scanning time ΔT_scan, the time needed for scanning laser frequency through the halfwidth Δν_HWHM of the absorption line, equal to or longer than 14 times of the LIA time constant τ is concluded in order to efficiently reduce the noise while without significant shift and distortion of the line shape. Experimental validation was carried out using a laser heterodyne absorption spectroscopy approach in the laboratory. Four different combinations of time constants τ and scanning time ΔT_scan were used to record heterodyne spectra of a CH₄ absorption line near 1242.00 cm⁻¹ in continuous laser tuning mode. An optimal combination of a scanning time of 137 ms with a time constant of 1 ms was obtained. This optimal combination was used for ground-based measurements of CH₄ and N₂O in the atmospheric column by LHR. The extracted LHR spectrum is in good agreement with a referenced TCCON (Total Carbon Column Observing Network) FT-IR (Fourier-transform infrared) spectrum. Full article