Comment on amt-2021-338

Operational retrievals of tropospheric trace gases from space-borne spectrometers are based on one-dimensional radiative transfer models. To minimize cloud effects, trace gas retrievals generally implement Lambertian cloud models based on radiometric cloud fraction estimates and photon path length corrections. The latter relies on measurements of the oxygen collision pair (O2-O2) absorption at 477 nm or on the oxygen A-band around 760 nm. In reality however, the impact of clouds is much more complex, involving unresolved sub-pixel clouds, scattering of clouds in neighboring pixels and cloud shadow effects, such that unresolved three-dimensional effects due to clouds may introduce significant biases in trace gas retrievals. In order to quantify this impact, we study NO2 as a trace gas example, and apply standard retrieval methods including approximate cloud corrections to synthetic data generated by the state-of-the-art three-dimensional Monte Carlo radiative transfer model MYSTIC. A sensitivity study is performed for simulations including a box-cloud, and the dependency on various parameters is investigated. The most significant bias is found for cloud shadow effects under polluted conditions. Biases depend strongly on cloud shadow fraction, NO2 profile, cloud optical thickness, solar zenith angle, and surface albedo. Several approaches to correct NO2 retrievals under cloud shadow conditions are explored. We find that air mass factors calculated using fitted surface albedo or corrected using the O2-O2 slant column density can partly mitigate cloud shadow effects. However, these approaches are limited to cloud-free pixels affected by surrounding clouds. A parameterization approach is presented based on relationships derived from the sensitivity study. This allows identifying measurements for which the standard NO2 retrieval produces a significant bias, and therefore provides a way to improve the current data flagging approach.

Algorithm for retrieving surface pressure from hyper-spectral measurements in oxygen A-band

Simulating irradiance enhancement dependence on cloud optical depth and solar zenith angle

Errors induced by the neglect of polarization in radiance calculations for three-dimensional cloudy atmospheres

<strong class="journal-contentHeaderColor">Abstract.</strong> Natural cirrus clouds and contrails cover about 30 % of the Earth's mid-latitudes and up to 70 % of its Tropics. Due to their widespread occurrence, cirrus have a considerable impact on the Earth energy budget, which, on average, leads to a warming net radiative effect (solar + thermal-infrared). However, whether the instantaneous radiative effect (RE) of natural cirrus or contrails is positive or negative depends on their microphysical, macrophysical, and optical, as well as radiative properties of the environment. This is further complicated by the fact that the actual ice crystal shape is often unknown and thus ice clouds remain one of the components that are least understood in the Earth's radiative budget. The present study aims to separate the effect on cirrus RE of eight parameters: solar zenith angle, ice water content, ice crystal effective radius, cirrus temperature, surface albedo, surface temperature, liquid water cloud optical thickness of an underlying cloud, and three ice crystal shapes. In total, 94,500 radiative transfer simulations have been performed, spanning the parameter ranges that are typically associated with natural cirrus and contrails. The multi-dimensionality and complexity of the 8-dimension parameter space makes it impractical to discuss all potential configurations in detail. Therefore, specific cases are selected and discussed. The ice crystal effective radius has the largest impact on solar, thermal-infrared (TIR), and net RE. The second most important parameter is the ice water content, which impacts the solar and terrestrial RE equally. Solar and TIR RE have opposite signs, meaning that the ice water content has a relatively small impact on net RE. Beyond the ice crystal effective radius and the ice water content, the solar RE of cirrus is determined by solar zenith angle, surface albedo, liquid cloud optical thickness, and the ice crystal shape in descending priority. RE in the TIR spectrum is dominated by the surface temperature, the ice cloud temperature, the liquid water cloud optical thickness, and the ice crystal shape. Net RE is controlled by the surface albedo, the solar zenith angle, and the surface albedo in decreasing importance. The relative importance of the studied parameters differs depending on the ambient conditions and during nighttime the net RE is equal to the TIR RE. The data set generated in this work is publicly available. It can be used to compute the radiative effect of cirrus clouds, contrails, and contrail cirrus instead of full radiative transfer calculations.

<strong class="journal-contentHeaderColor">Abstract.</strong> Natural cirrus clouds and contrails cover about 30 % of the Earth's mid-latitudes and up to 70 % of its Tropics. Due to their widespread occurrence, cirrus have a considerable impact on the Earth energy budget, which, on average, leads to a warming net radiative effect (solar + thermal-infrared). However, whether the instantaneous radiative effect (RE) of natural cirrus or contrails is positive or negative depends on their microphysical, macrophysical, and optical, as well as radiative properties of the environment. This is further complicated by the fact that the actual ice crystal shape is often unknown and thus ice clouds remain one of the components that are least understood in the Earth's radiative budget. The present study aims to separate the effect on cirrus RE of eight parameters: solar zenith angle, ice water content, ice crystal effective radius, cirrus temperature, surface albedo, surface temperature, liquid water cloud optical thickness of an underlying cloud, and three ice crystal shapes. In total, 94,500 radiative transfer simulations have been performed, spanning the parameter ranges that are typically associated with natural cirrus and contrails. The multi-dimensionality and complexity of the 8-dimension parameter space makes it impractical to discuss all potential configurations in detail. Therefore, specific cases are selected and discussed. The ice crystal effective radius has the largest impact on solar, thermal-infrared (TIR), and net RE. The second most important parameter is the ice water content, which impacts the solar and terrestrial RE equally. Solar and TIR RE have opposite signs, meaning that the ice water content has a relatively small impact on net RE. Beyond the ice crystal effective radius and the ice water content, the solar RE of cirrus is determined by solar zenith angle, surface albedo, liquid cloud optical thickness, and the ice crystal shape in descending priority. RE in the TIR spectrum is dominated by the surface temperature, the ice cloud temperature, the liquid water cloud optical thickness, and the ice crystal shape. Net RE is controlled by the surface albedo, the solar zenith angle, and the surface albedo in decreasing importance. The relative importance of the studied parameters differs depending on the ambient conditions and during nighttime the net RE is equal to the TIR RE. The data set generated in this work is publicly available. It can be used to compute the radiative effect of cirrus clouds, contrails, and contrail cirrus instead of full radiative transfer calculations.

Abstract. Retrievals of trace gas concentrations from satellite observations are mostly performed for clear regions or regions with low cloud coverage. However, even fully clear pixels can be affected by clouds in the vicinity, either by shadowing or by scattering of radiation from clouds in the clear region. Quantifying the error of retrieved trace gas concentrations due to cloud scattering is a difficult task. One possibility is to generate synthetic data by three-dimensional (3D) radiative transfer simulations using realistic 3D atmospheric input data, including 3D cloud structures. Retrieval algorithms may be applied on the synthetic data, and comparison to the known input trace gas concentrations yields the retrieval error due to cloud scattering. In this paper we present a comprehensive synthetic dataset which has been generated using the Monte Carlo radiative transfer model MYSTIC (Monte Carlo code for the phYSically correct Tracing of photons In Cloudy atmospheres). The dataset includes simulated spectra in two spectral ranges (400–500 nm and the O2A-band from 755–775 nm). Moreover it includes layer air mass factors (layer-AMFs) calculated at 460 nm. All simulations are performed for a fixed background atmosphere for various sun positions, viewing directions and surface albedos. Two cloud setups are considered: the first includes simple box clouds with various geometrical and optical thicknesses. This can be used to systematically investigate the sensitivity of the retrieval error on solar zenith angle, surface albedo and cloud parameters. Corresponding 1D simulations are also provided. The second includes realistic three-dimensional clouds from an ICON large eddy simulation (LES) for a region covering Germany and parts of surrounding countries. The scene includes cloud types typical of central Europe such as shallow cumulus, convective cloud cells, cirrus and stratocumulus. This large dataset can be used to quantify the trace gas concentration retrieval error statistically. Along with the dataset, the impact of horizontal photon transport on reflectance spectra and layer-AMFs is analysed for the box-cloud scenarios. Moreover, the impact of 3D cloud scattering on the NO2 vertical column density (VCD) retrieval is presented for a specific LES case. We find that the retrieval error is largest in cloud shadow regions, where the NO2 VCD is underestimated by more than 20 %. The dataset is available for the scientific community to assess the behaviour of trace gas retrieval algorithms and cloud correction schemes in cloud conditions with 3D structure.

Current and future satellite sensors provide measurements in and around the oxygen A-band on a global basis. These data are commonly used for the determination of cloud and aerosol properties. In this paper, we assess the information content in the oxygen A-band for the retrieval of macrophysical cloud parameters using precise radiative transfer simulations covering a wide range of geophysical conditions in conjunction with advance inversion techniques. The information content of the signal with respect to the retrieved parameters is analyzed in a stochastic framework using two common criteria: the degrees of freedom for a signal and the Shannon information content. It is found that oxygen A-band measurements with moderate spectral resolution (0.2 nm) provide two pieces of independent information that allow the accurate retrieval of cloud-top height together with either cloud optical thickness or cloud fraction. Additionally, our results confirm previous studies indicating that the retrieval of cloud geometrical thickness (CGT) from single-angle measurements is not reliable in this spectral region. Finally, a sensitivity study shows that the retrieval of macrophysical cloud parameters is slightly sensitive to the uncertainty in the CGT and very sensitive to the uncertainty in the surface albedo.

The knowledge of the surface reflectance is essential for the retrieval of atmospheric trace-gases from satellites. It is required in the conversion of the observed trace gas slant column to the total vertical column by means of a so-called air-mass factor. Although there exists climatological databases based on UV satellite data (e.g. OMI, GOME-2), these have a low spatial resolution and are not appropriate for current and future UV satellite missions like Sentinel-5p/TROPOMI or MTG-S/UVN (Sentinel-4) due their significantly higher spatial and spectral resolution. Current climatologies which are used in operational retrievals provide the Lambertian Equivalent Reflection (LER, e.g. OMI, GOME-2, TROPOMI, see [1,2,3]) and Directional-LER (DLER, e.g. GOME-2, TROPOMI see [3,4]) for selected wavelength in the UV-VIS range and are based on the so-called minimum LER approach, i.e. determine the minimum surface reflectance in the measurement timeframe.We present here a new technique called GE_LER (Geometry-dependent Effective Lambertian Equivalent Reflectivity) based on Machine Learning, which retrieves the DLER from UV satellites in a wavelength range as opposed to the single wavelength approaches of existing climatologies. In this way, dedicated surface reflectivities for specific trace gas retrieval wavelength ranges can be determined. We train a Neural Network with simulated UV spectra, which have been calculated with (V)LIDORT (see [5]). This radiative transfer model is also used for the generation of Air Mass Factors in the operational TROPOMI trace gas retrieval. In this way we reduce the influence of using different radiative transfer models with respect to trace gas retrievals.First results of our GE_LER retrieval for several trace-gases based on TROPOMI data will be shown.&amp;#160;References[1] Kleipool (2010), OMI/Aura Surface Reflectance Climatology L3 Global Gridded 0.5 degree x 0.5 degree V3, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC),, 10.5067/Aura/OMI/DATA3006[2] Tilstra et al. (2017), Surface reflectivity climatologies from UV to NIR determined from Earth observations by GOME-2 and SCIAMACHY, J. Geophys. Res. Atmos. 122, 4084-4111, doi:10.1002/2016JD025940[3] Tilstra et al. (2021), Directionally dependent Lambertian-equivalent reflectivity (DLER) of the Earth's surface measured by the GOME-2 satellite instruments, Atmos. Meas. Tech. 14, 4219-4238, doi:10.5194/amt-14-4219-2021[4] Tilstra et al. (2023), A directional surface reflectance climatology determined from TROPOMI observations, Atmos. Meas. Tech. Discuss. [preprint], doi:10.5194/amt-2023-222, in review[4] Spurr et al. (2008), LIDORT and VLIDORT: Linearized pseudo-spherical scalar and vector discrete ordinate radiative transfer models for use in remote sensing retrieval problems. Light Scattering Reviews, Volume 3, ed. A. Kokhanovsky, Springer

In this paper, we present an overview of the cloud property data set derived from 8 years of reflected solar ultraviolet-visible (UV-VIS) measurements taken by the global ozone monitoring experiment (GOME) instrument from April 1996 to June 2003. We consider four such properties: cloud amount, cloud-top pressure, cloud optical thickness and cloud type. Cloud amounts are generated from GOME broadband polarization data using data fusion techniques, while cloud-top height (pressure) and cloud-top albedo are retrieved from GOME backscatter measurements in the oxygen (O2) A-band via neural network inversion of simulated reflectances. Cloud optical thickness is derived as an additional parameter from the cloud-top albedo and radiative transfer model simulations, and cloud type is determined from the cloud-top pressure and optical thickness. We analyse global and seasonal patterns for these properties, looking at monthly means, standard deviations and the 8-year average values. We compare GOME results with the longer-period multisatellite international satellite cloud climatology project (ISCCP) D-series cloud climatology. The overall good agreement demonstrates that GOME provides accurate and complementary cloud information. Differences in cloud amount, cloud-top height and optical thickness values are due primarily to contrasting measurement strategies (GOME measures daytime-only UV-VIS backscatter, ISCCP is based on several day and night infrared satellite observations). We look forward to the extension of this UV-VIS cloud parameter series with the advent of more recent backscatter atmospheric composition instruments such as the scanning imaging absorption spectrometer for atmospheric cartography (SCIAMACHY) on-board the environmental satellite (ENVISAT) and the GOME-2 series on the MetOp platforms.

The gas-aerosol composition of the atmosphere determines specific features of the radiative net irradiance in the atmosphere and the associated climatic changes. The study discusses the anthropogenic variations in the content of the most important greenhouse gases, such as carbon dioxide (CO2) and ozone (O3), as well as the atmospheric aerosol. The estimates of their radiative effects (forcing, RF) in various geophysical conditions are given. Based on the modern ECRAD radiation model, the RF values of considered anthropogenic trace gases and aerosols over the past 20 years were estimated for different seasons of the year relative to their preindustrial level for the Moscow region. We determined specific features of the vertical profiles of RF in the shortwave and longwave spectral ranges and their values at the bottom (BOA) and the top of the atmosphere (TOA) depending on solar elevation and surface albedo, both taking seasonal variations into account and without them. The total RF Total for the warm period with a low surface albedo is negative (–8,33 W/m2 at BOA and –1,35 W/m2 at TOA) if seasonal variations of all considering trace gases and aerosols are taken into account. A weakly absorbing aerosol typical of mid-latitudes plays a significant role in the negative RF. The RF Total for the cold season is –0,08 W/m2 at BOA and +0,38 W/m2 at TOA. The positive value of the total RF at the TOA is due to the positive RF of the aerosol with its absorbing properties and the influence of the high albedo of snow surface, as well as due to the positive RF of carbon dioxide. A nonlinear RF dependence of the trace gases and aerosol on the solar elevation and surface albedo was found. The radiative heating rate due to greenhouse gases at TOA is negative in all seasons of the year. At the same time, it is positive at BOA (about 0,45 K/day in the warm season and 0,25 K/day in the cold season), mainly due to the absorption by aerosol in the lower layers of the troposphere. The radiative heating rate due to CO2 is slightly positive.

Carbon dioxide (CO2) is a major anthropogenic greenhouse gas. Atmospheric CO2 has increased from a preindustrial value of about 280 ppmv to more than 400 ppmv, mainly due to the fossil-fuel combustion and changes in land use. Understanding the CO2 distribution and variability of sources and sinks is essential for predicting changes in future CO2 concentration. However, in-situ measurements collected at a network of surface stations are sparse to allow the CO2 sources and sinks to be inferred. Satellite remote sensing is one of the best ways to obtain such global observations. The radiances reflected or transmitted by the atmosphere contain information about the atmospheric gases through their absorption signatures. High spectral radiance in the near-infrared 1.6 μm band, observed by OCO and Chinese TanSat, can be used to derive the CO2 column densities in the atmosphere. Surface reflection and atmospheric scattering processes act to reduce the intensity of radiation polarized in the direction parallel to the principal plane, as defined by the incoming solar beam and the beam entering the instrument. Both the OCO and TanSat instruments are typical polarizing instruments that are designed to measure only the radiation perpendicular to the principal plane; this will create a disparity between the simulation and measurements if polarization effects are neglected in forward modeling. In this paper, the US standard atmospheric profile with multiple layer aerosol loading is used to evaluate the forward-modeling error made by scalar approximations in the near-infrared 1.6 μm band. Numerical computations were performed using the line-by-line and doubling-adding methods. The atmosphere is assumed to be plane parallel and the surface is set to offer Lambert reflection. The polarizations introduced by molecular Rayleigh scattering and aerosol Mie scattering are calculated respectively. Solar zenith angle, view zenith angle, surface-reflectance, and aerosol optical depth are varied one at a time to evaluate the individual errors. The results show that, except for some situations with very large observation angles, the radiation error made by the scalar approximation increases with the solar zenith angle, increase in aerosol optical depth, and decrease in the surface reflectance. The errors in the line cores are larger than those in the window area because they are affected less by the surface depolarization effect in the absorption channels. For both OCO and TanSat, the conventional nonlinear least-squares-fitting technique, by which the forward model calculation is fit to satellite observations, is used to obtain the CO2 column information. The atmospheric CO2 information comes mainly from the radiation ratio between the absorption and window channels, which means that the radiance-simulation error will be translated into errors in CO2 column retrieval. To assess these retrieval errors while ignoring the polarization effect in forward mode calculation, sensitivity studies are performed on simulated spectroscopic measurements in the 1.6 μm band. The CO2-retrieval errors arising from neglecting the polarization effect are seen to be largest when the solar zenith angle is high, the aerosol optical depth is large, and the surface reflectance is low. When the solar zenith angle is larger than 45°, the aerosol optical depth is higher than 0.3 and the surface albedo is less than 0.2; this carbon-dioxide retrieval error could be larger than 1–2 ppmv. Sometimes, this error may be as high as 10 ppmv, making it very large than what is required. The retrieval error budget could thus potentially be dominated by polarization. Thus, to reduce such errors, the forward model needs to take account of fully polarized radiation calculations. On the other hand, it is impractical to do full vector retrieval due to the computational cost. We need to devise ways to quickly complete the polarization radiative-transfer calculation.

Evaluation of satellite-based algorithms to estimate photosynthetically available radiation (PAR) reaching the ocean surface at high northern latitudes

Author(s): Dong, X; Xi, B; Qiu, S; Minnis, P; Sun-Mack, S; Rose, F | Abstract: Retrievals of cloud microphysical properties based on passive satellite imagery are especially difficult over snow-covered surfaces because of the bright and cold surface. To help quantify their uncertainties, single-layered overcast liquid-phase Arctic stratus cloud microphysical properties retrieved by using the Clouds and the Earth’s Radiant Energy System Edition 2 and Edition 4 (CERES Ed2 and Ed4) algorithms are compared with ground-based retrievals at the Atmospheric Radiation Measurement North Slope of Alaska (ARM NSA) site at Barrow, AK, during the period from March 2000 to December 2006. A total of 206 and 140 snow-free cases (Rsfc ≤ 0.3), and 108 and 106 snow cases (Rsfcg0.3), respectively, were selected from Terra and Aqua satellite passes over the ARM NSA site. The CERES Ed4 and Ed2 optical depth (t) and liquid water path (LWP) retrievals from both Terra and Aqua are almost identical and have excellent agreement with ARM retrievals under snow-free and snow conditions. In order to reach a radiation closure study for both the surface and top of atmosphere (TOA) radiation budgets, the ARM precision spectral pyranometer-measured surface albedos were adjusted (63.6% and 80% of the ARM surface albedos for snow-free and snow cases, respectively) to account for the water and land components of the domain of 30 km × 30 km. Most of the radiative transfer model calculated SW↓sfc and SW↑TOA fluxes by using ARM and CERES cloud retrievals and the domain mean albedos as input agree with the ARM and CERES flux observations within 10Wm-2 for both snow-free and snow conditions. Sensitivity studies show that the ARM LWP and re retrievals are less dependent on solar zenith angle (SZA), but all retrieved optical depths increase with SZA.

New Directions: A facelift for the picture of the global energy balance