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The COVID‐19 pandemic led to a 72% reduction of air traffic over Europe in March–August 2020 compared to 2019. Modeled contrail cover declined similarly, and computed mean instantaneous radiative contrail forcing dropped regionally by up to 0.7 W m−2. Here, model predictions of cirrus optical thickness and the top‐of‐atmosphere outgoing longwave and reflected shortwave irradiances are tested by comparison to Meteosat‐SEVIRI‐derived data. The agreement between observations and modeled data is slightly better when modeled contrail cirrus contributions are included. The spatial distributions and diurnal cycles of the differences in these data between 2019 and 2020 are partially caused by differences in atmospheric and surface conditions, particularly for solar radiation in the spring of 2020. Aviation signals become discernible in the observed differences of these data between 2019 and 2020 when subtracting numerical weather prediction model results that approximate the atmosphere and surface conditions without contrails. Plain Language Summary: Aircraft flying in cold and humid air masses induce contrails which warm the Earth‐atmosphere system by reducing the terrestrial radiation out into space and cool by increasing the Earth's albedo. Previous studies found that the warming effects dominate and that contrails may contribute most of the present radiative forcing of climate change induced by aviation. The COVID‐19 pandemic led to a worldwide and long‐duration reduction of air traffic. This paper compares model predictions and satellite‐observed cirrus properties and irradiances over Europe for 6 months in 2019 and 2020. The models account for changes in the atmosphere and at the Earth's surface in the two half‐years. Model and observation results show about 90% correlation and 20% mean normalized deviations. The agreement between observed and modeled optical cirrus thickness and terrestrial irradiances improves slightly when the modeled contrail cirrus contributions are included. Solar radiation changes show a larger variability because of large changes in the lower atmosphere and at the Earth surface. Since worldwide traffic activity has stayed at low levels after August 2020, the comparisons may be extended. Further model studies, including the effects of other emissions, are needed for a more comprehensive understanding of the observed changes. Key Points: Air traffic reduction during the COVID‐19 pandemic is used for testing aviation contrail cirrus and related radiative forcing modelingCirrus optical depth and top‐of‐atmosphere irradiances from satellite observations and model results show reasonable correlationsAviation contrail signatures are identifiable in spite of strongly different atmosphere and surface conditions in 2019 and 2020 [ABSTRACT FROM AUTHOR]

In this study, a substantially improved version of the Meteosat cirrus detection algorithm (MeCiDA2) will be presented, which now allows application to the full earth disc visible by the Meteosat satellite. As cirrus clouds have an influence on the radiation budget of the earth, their optical properties and their global coverage has to be monitored at the global scale using instruments aboard geostationary satellites. Since MeCiDA was optimised for the area of Europe only, various changes were necessary to handle the variable conditions found over the full Meteosat disc. Required changes include the consideration of the viewing angle dependency and of the sensitivity of the 9.7 μm channel to the ozone column. To this end, a correction is implemented that minimises the influence of the variability of the stratospheric ozone. The evaluation of the proposed improvements is carried out by using MeCiDA applied to MODIS (moderate resolution imaging spectrometer) data to address viewing angledependent cirrus detection, and by additionally comparing it to the cloud optical properties MOD06 cirrus product. The new MeCiDA version detects less cirrus than the original one for latitudes larger than 40°, but almost the same amount elsewhere. MeCiDA's version for MODIS is more sensitive than that for SEVIRI (spinning enhanced visible and infrared imager) with cirrus occurrences higher by 10 %, and the new MeCiDA provides almost the same cirrus coverage (±0.1) as given by the cloud phase optical properties from MODIS for latitudes smaller than 50°. Finally, the influence of sub-pixel clouds on the SEVIRI cirrus detection has been examined: more than 60% of the undetected SEVIRI cirrus pixels have a cirrus coverage smaller than 0.5. [ABSTRACT FROM AUTHOR]

The article presents a study on an enhanced detection algorithm for cirrus clouds, validated using Moderate Resolution Imaging Spectroradiometer (MODIS). The study used various methods such as the estimation of the effects of stratospheric ozone amount on brightness temperature, remote sensing and Gaussian convolution kernel. It concludes that it is vital to monitor cirrus coverage due to its role in climate.

The article presents a study which provides ground-based observations of contrails and cirrus clouds caused by air traffic. The study visually analysed a six-month series of high-level clouds and contrails occurrence using an all-sky camera. It observed a contrail occurrence of 21% and a cirrus occurrence of 27% at daytime to 48% at nighttime. It also compared images gathered with data from advanced very high resolution radiometers (AVHRR) and SEVIRI satellites.

libRadtran is a widely used software package for radiative transfer calculations. It allows to compute (polarized) radiances, irradiances, and actinic fluxes in the solar and thermal spectral regions. libRadtran has been used for various applications, including remote sensing of clouds, aerosols and trace gases in the Earth's atmosphere, climate studies, e.g., for the calculation of radiative forcing due to different atmospheric components, for UV-forcasting, the calculation of photolysis frequencies, and for remote sensing of other planets in our solar system. The package has been described in Mayer and Kylling (2005).. Since then several new features have been included, for example polarization, Raman scattering, a new molecular gas absorption parameterization, and several new cloud and aerosol scattering parameterizations. Furthermore a graphical user interface is now available which greatly simplifies the usage of the model, especially for new users. This paper gives an overview of libRadtran version 2.0 with focus on new features. A complete description of libRadtran and all its input options is given in the user manual included in the libRadtran software package, which is freely available at http://www.libradtran.org. [ABSTRACT FROM AUTHOR]

The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) – a crucial parameter to estimate the thermal cloud radiative forcing – can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud–Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 km lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0.90. The average CTHs derived by the SEVIRI algorithms are closer to the CPR measurements than to CALIOP measurements. The biases between SEVIRI and CPR retrievals range from −0.8 km to 0.6 km. The correlation coefficients of CPR and SEVIRI observations vary between 0.82 and 0.89. To discuss the origin of the CTH deviation, we investigate three cloud categories: optically thin and thick single layer as well as multi-layer clouds. For optically thick clouds the correlation coefficients between the SEVIRI and the reference data sets are usually above 0.95. For optically thin single layer clouds the correlation coefficients are still above 0.92. For this cloud category the SEVIRI algorithms yield CTHs that are lower than CALIOP and similar to CPR observations. Most challenging are the multi-layer clouds, where the correlation coefficients are for most algorithms between 0.6 and 0.8. Finally, we evaluate the performance of the SEVIRI retrievals for boundary layer clouds. While the CTH retrieval for this cloud type is relatively accurate, there are still considerable differences between the algorithms. These are related to the uncertainties and limited vertical resolution of the assumed temperature profiles in combination with the presence of temperature inversions, which lead to ambiguities in the CTH retrieval. Alternative approaches for the CTH retrieval of low clouds are discussed. [ABSTRACT FROM AUTHOR]