Line-by-line Radiative Transfer Model Research Articles

Performance of the Atmospheric Radiative Transfer Simulator (ARTS) in the 600–1650 cm−1 Region

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.

Evaluation of the Accuracy of Spectral Calibration Light Source on Spectral Radiance Acquired by the Greenhouse-Gases Absorption Spectrometer-2 (GAS-2)

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 μm (strong-CO2) 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.

GBB-Nadir and KLIMA: Two Full Physics Codes for the Computation of the Infrared Spectrum of the Planetary Radiation Escaping to Space

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.

Integrated efficient radiative transfer model named Dayu for simulating the imager measurements in cloudy atmospheres.

Rapid radiative transfer models are crucial to remote sensing and data assimilation. An integrated efficient radiative transfer model named Dayu, which is an updated version of the Efficient Radiative Transfer Model (ERTM) is developed to simulate the imager measurements in cloudy atmospheres. In Dayu model, the Optimized alternate Mapping Correlated K-Distribution model (OMCKD) which is predominant in dealing with the overlap of multiple gaseous lines is employed to efficiently calculate the gaseous absorption. The cloud and aerosol optical properties are pre-calculated and parameterized by the particle effective radius or length. Specifically, the ice crystal model is assumed as a solid hexagonal column, of which the parameters are determined based on massive aircraft observations. For the radiative transfer solver, the original 4-stream Discrete ordinate aDding Approximation (4-DDA) is extended to 2N-DDA (2N is the number of streams) which can calculate not only the azimuthally dependent radiance in the solar spectrum (including solar and infrared spectra overlap) but also the azimuthally averaged radiance in the thermal infrared spectrum through a unified adding method. Then the accuracy and efficiency of Dayu model are evaluated by comparing it with the benchmark model, i.e., Line-By-Line Radiative Transfer Model (LBLRTM) and DIScrete Ordinate Radiative Transfer (DISORT). Under the standard atmospheric profile, the maximum relative biases between Dayu model with 8-DDA / 16-DDA and the benchmark model (OMCKD with 64-stream DISORT) are 7.63% / 2.62% at solar channels but decreased to 2.66% / 1.39% at spectra-overlapping channel (3.7 μm). The computational efficiency of Dayu model with 8-DDA / 16-DDA is approximately three / two orders of magnitude higher than that of the benchmark model. At thermal infrared channels, the brightness temperature (BT) differences between Dayu model with 4-DDA and the benchmark model (LBLRTM with 64-stream DISORT) are bounded by 0.65K. Compared to the benchmark model, Dayu model with 4-DDA improves the computational efficiency by five orders of magnitude. In the application to the practical Typhoon Lekima case, the simulated reflectances and BTs by Dayu model have a high consistency with the imager measurements, demonstrating the superior performance of Dayu model in satellite simulation.

Ground-based remote sensing of aerosol properties using high-resolution infrared emission and lidar observations in the High Arctic

Abstract. Arctic amplification, the phenomenon that the Arctic is warming faster than the global mean, is still not fully understood. The Transregional Collaborative Research Centre “TRR 172: ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3” program, funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), contributes towards this research topic. For the purpose of measuring aerosol components, a Fourier transform infrared spectrometer (FTIR), for measuring downwelling emission (in operation since 2019), and a Raman lidar are operated at the joint Alfred Wegener Institute for Polar and Marine Research and Paul Emile Victor Institute (AWIPEV) research base in Ny-Ålesund, Spitsbergen (79∘ N, 12∘ E). To carry out aerosol retrieval using measurements from the FTS, the LBLDIS retrieval algorithm, based on a combination of the Line-by-Line Radiative Transfer Model (LBLRTM) and the DIScrete Ordinate Radiative Transfer (DISORT) algorithm, is modified for different aerosol types (dust, sea salt, black carbon, and sulfate), aerosol optical depth (AOD), and effective radius (Reff). Using lidar measurement, an aerosol and cloud classification method is developed to provide basic information about the distribution of aerosols or clouds in the atmosphere and is used as an indicator to perform aerosol or cloud retrievals with the FTS. Therefore, a two-instrument joint-observation scheme is designed and subsequently used on the data measured from 2019 to the present. In order to introduce this measurement technique in detail, an aerosol-only case study is presented using data from 10 June 2020. In the aerosol-only case, the retrieval results show that sulfate is the dominant aerosol throughout the day (τ900cm-1 = 0.007 ± 0.0027), followed by dust (τ900cm-1 = 0.0039 ± 0.0029) and black carbon (τ900cm-1 = 0.0017 ± 0.0007). Sea salt (τ900cm-1 = 0.0012 ± 0.0002), which has the weakest emission ability in the infrared wave band, shows the lowest AOD value. Such proportions of sulfate, dust, and BC also show good agreement with Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) reanalysis data. Additionally, comparison with a Sun photometer (AErosol RObotic NETwork – AERONET) shows the daily variation in the AOD retrieved from FTS to be similar to that retrieved by Sun photometer. Using this method, long-term observations (from April to August 2020) are retrieved and presented. We find that sulfate is often present in the Arctic; it is higher in spring and lower in summer. Similarly, BC is also frequently observed in the Arctic, with less obvious seasonal variation than sulfate. A BC outburst event is observed each spring and summer. In spring, sulfate and BC are dominant, whereas sea salt and dust are relatively low. In addition, a sea salt enhancement event is observed in summertime, which might be due to the melting of sea ice and emissions from nearby open water. From the retrieved results over a long time period, no clear correlations are found; thus, the aforementioned species can be retrieved independently of one another.

A Simple Analytical Model for THz Band Path Loss

In this letter, we devise a frequency, distance, and altitude-dependent, analytical model for THz band path loss. This model is obtained from cascaded regression of transmittance data from Line-by-Line Radiative Transfer Model (LBLRTM) propagation analysis tool, considering altitudes from the sea-level to 1 km, distances from 1 m to 100 m and frequencies within 0.79-0.91 THz and 0.93-0.94 THz. The proposed approach yields high accuracy with respect to propagation data while providing a simple, closed-form expression to help the design of Terahertz (THz) band drone communications.

Synergistic Retrieval of Temperature and Humidity Profiles from Space-Based and Ground-Based Infrared Sounders Using an Optimal Estimation Method

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.

Distributed Feedback Interband Cascade Laser Based Laser Heterodyne Radiometer for Column Density of HDO and CH4 Measurements at Dunhuang, Northwest of China

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.

Efficient line-by-line technique for calculating accurate and compact spectral lookup tables for satellite remote sensing

ABSTRACT This paper presents an efficient line-by-line (LBL) technique for the fast computation of compact and precise spectral lookup tables (LUTs) for LBL radiative transfer models. The key feature of this technique is obtaining and using efficient non-uniform wavenumber grids for line profile interpolations with a given accuracy. Grid points are concentrated at the centre of the lines and are rare in the wings. In case of narrow and isolated spectral lines, this technique derives LUTs that are compact by several orders of magnitude than those that use uniform grids. The potential of this technique is demonstrated using the problem of calculating non-Voigt line profiles, as suggested by Hartmann and Tran (HTP). The size of LUTs for the replacement of direct calculations of HTPs in forward remote sensing models is estimated, and a set of LUTs for H2O lines are created and written as ASCII files in http://wadis.saga.iao.ru/view/hartmann-tran/. Furthermore, the conditions under which this technique can speed up (by approximately one order of magnitude) forward LBL models are discussed.

Efficient radiative transfer model for thermal infrared brightness temperature simulation in cloudy atmospheres.

An efficient radiative transfer model (ERTM) is developed to simulate thermal infrared brightness temperatures observed by the Advanced Himawari Imager (AHI) in this study. The ERTM contains an alternate mapping correlated k-distribution (AMCKD) scheme, a parameterization for cloud optical property, and a rapid infrared radiative transfer scheme. The AMCKD is employed to calculate the gaseous absorption in the inhomogeneous thermodynamic atmosphere. The optical properties of clouds are parameterized by the effective length for ice clouds based on the Voronoi model, and by the effective radius for water clouds based on the Lorenz-Mie theory. The adding method of four-stream discrete ordinates method (4DDA) is extended to be able to calculate the thermal infrared radiative intensity varying with the zenith angle in ERTM. The efficiency and accuracy of ERTM are evaluated by comparing with the benchmark model which is composed of discrete ordinate radiative transfer (DISORT) and line-by-line radiative transfer model (LBLRTM). Under the standard atmospheric profiles, the root mean square error (RMSE) of simulated brightness temperatures reaches a maximum of 0.21K at the B16 (13.28 µm) channel of AHI. The computational efficiency of ERTM is approximately five orders of magnitude higher than that of the benchmark model. Moreover, the simulated brightness temperatures by ERTM are highly consistent with the rigorous results and AHI observations in the application to the Typhoon Mujigae case.

Terahertz communications at various atmospheric altitudes

Terahertz communications offers a massive potential for the prospective beyond 5G wireless systems, as the band offers huge bandwidth and data rates as compared to the existing sub 6 GHz bands, which are almost saturated. In this paper, we investigate the feasibility of wireless communications over the Terahertz-band (0.75–10 THz) at various atmospheric altitudes, considering different transmission distances and directions by realistically calculating the absorption loss, which is the major limiting factor affecting the propagation of THz waves through the earth’s atmosphere. Four practical altitudes are considered, corresponding to Drone-to-Drone (D2D), Jet plane-to-Jet plane (J2J), Unmanned Aerial Vehicle (UAV)-to-UAV, and near-space Satellite-to-Satellite (S2S) communications. Following comparison and validation with two real-world experimental results from the literature measured at the sea-level, Line by Line Radiative Transfer Models (LBLRTM) is used to obtain realistic THz-band transmittance values against each altitude case and setting. Subsequently, absorption loss and total path loss values are computed and mean total path loss sensitivity is further observed against a range of transmission directions via zenith angle variations from vertically-up to vertically-down communication. Numerical results show that as the altitude increases, the concentration of the water vapor molecules decreases, enabling the communication over the THz-band (0.75–10 THz) to be more feasible as compared to the sea-level communication. Moreover, the total usable bandwidth results over the THz-band (0.75–10 THz) exhibit that the upper bounds of 8.218 THz, 9.142 THz and 9.25 THz are usable up to the transmission distance of 2 km against the total antenna gains of 80 dBi for J2J, U2U and S2S communication cases, respectively.

Alternate Mapping Correlated k-Distribution Method for Infrared Radiative Transfer Forward Simulation

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.

Correcting for trace gas absorption when retrieving aerosol optical depth from satellite observations of reflected shortwave radiation

Abstract. Retrieving aerosol optical depth (AOD) from top-of-atmosphere (TOA) satellite-measured radiance requires separating the aerosol signal from the total observed signal. Total TOA radiance includes signal from the underlying surface and from atmospheric constituents such as aerosols, clouds and gases. Multispectral retrieval algorithms, such as the dark-target (DT) algorithm that operates upon the Moderate Resolution Imaging Spectroradiometer (MODIS, on board Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, on board Suomi-NPP) sensors, use wavelength bands in “window” regions. However, while small, the gas absorptions in these bands are non-negligible and require correction. In this paper, we use the High-resolution TRANsmission (HITRAN) database and Line-By-Line Radiative Transfer Model (LBLRTM) to derive consistent gas corrections for both MODIS and VIIRS wavelength bands. Absorptions from H2O, CO2 and O3 are considered, as well as other trace gases. Even though MODIS and VIIRS bands are “similar”, they are different enough that applying MODIS-specific gas corrections to VIIRS observations results in an underestimate of global mean AOD (by 0.01), but with much larger regional AOD biases of up to 0.07. As recent studies have been attempting to create a long-term data record by joining multiple satellite data sets, including MODIS and VIIRS, the consistency of gas correction has become even more crucial.

Vertical profile of tropospheric ozone derived from synergetic retrieval using three different wavelength ranges, UV, IR, and microwave: sensitivity study for satellite observation

Abstract. We performed a feasibility study of constraining the vertical profile of the tropospheric ozone by using a synergetic retrieval method on multiple spectra, i.e., ultraviolet (UV), thermal infrared (TIR), and microwave (MW) ranges, measured from space. This work provides, for the first time, a quantitative evaluation of the retrieval sensitivity of the tropospheric ozone by adding the MW measurement to the UV and TIR measurements. Two observation points in East Asia (one in an urban area and one in an ocean area) and two observation times (one during summer and one during winter) were assumed. Geometry of line of sight was nadir down-looking for the UV and TIR measurements, and limb sounding for the MW measurement. The retrieval sensitivities of the ozone profiles in the upper troposphere (UT), middle troposphere (MT), and lowermost troposphere (LMT) were estimated using the degree of freedom for signal (DFS), the pressure of maximum sensitivity, reduction rate of error from the a priori error, and the averaging kernel matrix, derived based on the optimal estimation method. The measurement noise levels were assumed to be the same as those for currently available instruments. The weighting functions for the UV, TIR, and MW ranges were calculated using the SCIATRAN radiative transfer model, the Line-By-Line Radiative Transfer Model (LBLRTM), and the Advanced Model for Atmospheric Terahertz Radiation Analysis and Simulation (AMATERASU), respectively. The DFS value was increased by approximately 96, 23, and 30 % by adding the MW measurements to the combination of UV and TIR measurements in the UT, MT, and LMT regions, respectively. The MW measurement increased the DFS value of the LMT ozone; nevertheless, the MW measurement alone has no sensitivity to the LMT ozone. The pressure of maximum sensitivity value for the LMT ozone was also increased by adding the MW measurement. These findings indicate that better information on LMT ozone can be obtained by adding constraints on the UT and MT ozone from the MW measurement. The results of this study are applicable to the upcoming air-quality monitoring missions, APOLLO, GMAP-Asia, and uvSCOPE.

Consistency between GRUAN sondes, LBLRTM and IASI

Abstract. Radiosonde soundings from the GCOS Reference Upper-Air Network (GRUAN) data record are shown to be consistent with Infrared Atmospheric Sounding Instrument (IASI)-measured radiances via LBLRTM (Line-By-Line Radiative Transfer Model) in the part of the spectrum that is mostly affected by water vapour absorption in the upper troposphere (from 700 hPa up). This result is key for climate data records, since GRUAN, IASI and LBLRTM constitute reference measurements or a reference radiative transfer model in each of their fields. This is specially the case for night-time radiosonde measurements. Although the sample size is small (16 cases), daytime GRUAN radiosonde measurements seem to have a small dry bias of 2.5 % in absolute terms of relative humidity, located mainly in the upper troposphere, with respect to LBLRTM and IASI. Full metrological closure is not yet possible and will not be until collocation uncertainties are better characterized and a full uncertainty covariance matrix is clarified for GRUAN.

Measurements of downwelling far-infrared radiance during the RHUBC-II campaign at Cerro Toco, Chile and comparisons with line-by-line radiative transfer calculations

Downwelling radiances at the Earth's surface measured by the Far-Infrared Spectroscopy of the Troposphere (FIRST) instrument in an environment with integrated precipitable water (IPW) as low as 0.03cm are compared with calculated spectra in the far-infrared and mid-infrared. FIRST (a Fourier transform spectrometer) was deployed from August through October 2009 at 5.38km MSL on Cerro Toco, a mountain in the Atacama Desert of Chile. There FIRST took part in the Radiative Heating in Unexplored Bands Campaign Part 2 (RHUBC-II), the goal of which is the assessment of water vapor spectroscopy. Radiosonde water vapor and temperature vertical profiles are input into the Atmospheric and Environmental Research (AER) Line-by-Line Radiative Transfer Model (LBLRTM) to compute modeled radiances. The LBLRTM minus FIRST residual spectrum is calculated to assess agreement. Uncertainties (1-σ) in both the measured and modeled radiances are also determined. Measured and modeled radiances nearly all agree to within combined (total) uncertainties. Features exceeding uncertainties can be corrected into the combined uncertainty by increasing water vapor and model continuum absorption, however this may not be necessary due to 1-σ uncertainties (68% confidence). Furthermore, the uncertainty in the measurement-model residual is very large and no additional information on the adequacy of current water vapor spectral line or continuum absorption parameters may be derived. Similar future experiments in similarly cold and dry environments will require absolute accuracy of 0.1% of a 273K blackbody in radiance and water vapor accuracy of ∼3% in the profile layers contributing to downwelling radiance at the surface.

Laboratory spectral calibration of TanSat and the influence of multiplex merging of pixels

ABSTRACTThis article first reviews the main characteristics of the High-Resolution Hyperspectral Sensor for carbon observation Grating Spectrometer (HRHS-GS) and discusses the impact of spectral resolution on gas absorption lines. The major content of this article is the laboratory calibration of HRHS-GS, the signal-to-noise ratio (SNR), instrument line shape (ILS), and the spectral resolution of each channel were achieved. The SNR results met the mission requirements for the 0.76 µm band, but missed the requirement for the two Carbon dioxide (CO2) bands. To address this problem, the model ‘Multiplex Merging of Spectral Pixels’ was established to improve the SNR by increasing the incident energy of a single spectral channel. This process would lead to spectral broadening; the spectral resolution before and after that process was obtained. The transmittance spectra before and after multiplex merging were compared by the line-by-line radiative transfer model (LBLRTM) to analyse the impact of spectral broadening on gas absorption lines. Next, the results were verified by experiment with a gas absorption cell. The results showed that ‘Multiplex Merging of Spectral Pixels’ could effectively improve the SNR. For the 0.76 µm band, the transmittance spectra before and after multiplex merging were almost the same; for the 1.61 µm band, the peak value of the transmittance spectra decays by about 5%; and for the 2.06 µm band, the attenuation of the transmittance spectra is smaller than 3%. Meanwhile, the spectral resolution after spectral broadening still satisfied the study’s requirement.

Simultaneous retrieval of water vapour, temperature and cirrus clouds properties from measurements of far infrared spectral radiance over the Antarctic Plateau

Abstract. The possibility separating the contributions of the atmospheric state and ice clouds by using spectral infrared measurements is a fundamental step to quantifying the cloud effect in climate models. A simultaneous retrieval of cloud and atmospheric parameters from infrared wideband spectra will allow the disentanglement of the spectral interference between these variables. In this paper, we describe the development of a code for the simultaneous retrieval of atmospheric state and ice cloud parameters, and its application to the analysis of the spectral measurements acquired by the Radiation Explorer in the Far Infrared – Prototype for Applications and Development (REFIR-PAD) spectroradiometer, which has been in operation at Concordia Station on the Antarctic Plateau since 2012. The code performs the retrieval with a computational time that is comparable with the instrument acquisition time. Water vapour and temperature profiles and the cloud optical and microphysical properties, such as the generalised effective diameter and the ice water path, are retrieved by exploiting the 230–980 cm−1 spectral band. To simulate atmospheric radiative transfer, the Line-By-Line Radiative Transfer Model (LBLRTM) has been integrated with a specifically developed subroutine based on the δ-Eddington two-stream approximation, whereas the single-scattering properties of cirrus clouds have been derived from a database for hexagonal column habits. In order to detect ice clouds, a backscattering and depolarisation lidar, co-located with REFIR-PAD has been used, allowing us to infer the position and the cloud thickness to be used in the retrieval. A climatology of the vertical profiles of water vapour and temperature has been performed by using the daily radiosounding available at the station at 12:00 UTC. The climatology has been used to build an a priori profile correlation to constrain the fitting procedure. An optimal estimation method with the Levenberg–Marquardt approach has been used to perform the retrieval. In most cases, the retrieved humidity and temperature profiles show a good agreement with the radiosoundings, demonstrating that the simultaneous retrieval of the atmospheric state is not biased by the presence of cirrus clouds. Finally, the retrieved cloud parameters allow us to study the relationships between cloud temperature and optical depth and between effective particle diameter and ice water content. These relationships are similar to the statistical correlations measured on the Antarctic coast at Dumont d'Urville and in the Arctic region.

Approaches for hyperspectral remote flux quantification and visualization of GHGs in the environment

Methane (CH4) and nitrous oxide (N2O) are two very potent greenhouse gases, with highly heterogeneous distributions in both space and time. Mapping hot-spots and source areas, and measuring fluxes in different environments has so far not been possible on a local scale using direct measurements. We have developed a method for simultaneous mapping of methane (CH4) and nitrous oxide (N2O), also including water vapor (H2O), using ground-based remote sensing on a landscape-sized scale by utilizing Imaging Fourier Transform Spectrometers (IFTS) with high spectral resolution and imaging rates. The approach uses calculated libraries of transmission spectra at the spectroscopic resolutions of the IFTS, based on the HITRAN database of spectroscopic lines and our own line-by-line radiative transfer model (LBLRTM). For each species, 1024 spectra have been made, resulting in 10243 combinations of column densities. Using an adaptive grid, solutions are found for each line of sight at a spectral resolution of up to 0.25cm−1 using the full spectral region of the detector. The modeling is multi-layered, calculating temperatures of the background, air, and any additional gas layers, also accounting for reflected cold sky. Background distances can be mapped from the amount of water vapor in each line of sight. The described approach can be used to identify sources, quantify gas distributions, and to calculate fluxes. Visualizations can produce gas distribution images, as well as air motion videos, which are used to map fluxes using the same data set, without the need for additional instruments for wind measurements.

Inhomogeneous Radiative Forcing of NF3

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.